{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","employer_pilot_url":"https://aidevboard.com/verified-interview-pilot","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"candidate_resume_action":{"application_authorized":false,"candidate_charge":0,"endpoint":"https://aidevboard.com/api/v1/candidate/resume-preview","job_id_json_path":"jobs[].id","method":"POST","preview_requires_identity":false,"required_body_fields":["job_id","evidence_bullets"],"requires_explicit_human_review":true,"saved_artifact_protocol":"mcp","saved_artifact_requires_verified_human":true,"saved_artifact_tool":"compile_job_specific_resume","search_requires_identity":false,"status":"available_after_candidate_selects_job","submission_performed":false,"uses_candidate_verified_evidence":true},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"6e489569-b334-49ce-8208-039de04ea5ce","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Research Scientist, RL for Autonomous Planning \u0026 World Modeling  ","slug":"research-scientist-rl-for-autonomous-planning-world-modeling-adc21b92","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. \n In this hybrid role, you will report to a Principal Scientist.\n You will: \n \n Participate in Waymo’s Foundation World Model post-training and evaluation\n Research and develop cutting edge RL and Distillation techniques for Autonomous Vehicle Trajectory Planning\n Integrate emerging research from the broader AI community into Waymo’s internal RL infrastructure, conducting rigorous ablations to identify and scale the most promising methods\n Partner with engineering and research teams across Waymo to share recipes, techniques, and post-training best practices to accelerate our collective know-how\n \n You have: \n \n PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar technical field; with 3+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models\n Demonstration of original contributions to the field through high-impact publications (ArXiv, peer-reviewed conferences like NeurIPS/ICLR/CVPR), technical blog posts, or significant open-source contributions\n Proficiency in implementing model training flows in a scalable, distributed and performant manner such as Data parallel, FSDP and other sharding approaches\n A willingness to work with complexity of globally distributed inference infrastructure\n \n We prefer: \n \n PhD in Computer Science, Machine Learning, or Robotics, with a research focus on Reinforcement Learning, Foundation Models, or Multi-Modal learning\n Extensive experience designing and deploying Reinforcement Learning infrastructure, specifically for on-policy learning or alignment with human preferences\n A consistent history of original contributions to the AI community, evidenced by first-author publications at top-tier venues (e.g., NeurIPS, ICLR, ICRA) or maintaining significant open-source ML projects\n Experience with large scale (many-machine) training infrastructure and techniques for inference with large models such as model sharding/tensor-parallel\n \n In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:\n \n Health, dental, vision, life, disability insurance\n Retirement Benefits: 401(k) with company match\n Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment\n Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)\n Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks\n Baby Bonding Leave: 18 weeks\n Holidays: 13 paid days per year\n \n Please note that Waymo may not be able to employ remotely in all locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process\n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $204,000 — $259,000 USD","salary_min":204000,"salary_max":259000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["reinforcement-learning","autonomous-vehicles","generative-ai","robotics","research"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8165872","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-30T02:06:16Z","expires_at":"2026-09-29T13:35:05.501784Z","created_at":"2026-08-30T13:35:05.638136Z","updated_at":"2026-08-30T13:35:05.638136Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6e489569-b334-49ce-8208-039de04ea5ce"},{"id":"4ab10eb7-b0f8-4543-87e5-430128653c2a","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Lead, Cyber Harms","slug":"safeguards-enforcement-lead-cyber-harms-3ea20726","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n As an Enforcement Lead, you will be responsible for managing and executing enforcement actions across our products and services, with a focus on detecting and mitigating attempts to misuse Anthropic's AI systems for malicious cyber operations. Your work will center on developing strategic enforcement frameworks for flagged activity related to cyberattacks, malware development, and offensive exploitation. Additionally, you will manage a team of Cyber Enforcement Analysts and contractors implementing this enforcement strategy. \n Safety is core to our mission, and you'll help uphold policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.\n Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a violent, technical, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays.\n Key responsibilities\n \n \n Manage a team of Cyber Enforcement Analysts and contractors, overseeing the vision of Cyber Enforcement strategy \n \n Create strategies to detect and mitigate potential misuse of AI systems to facilitate cyberattacks, malware creation, exploitation tooling, and related harmful cyber operations\n \n Collaborate with stakeholders regarding novel, ambiguous, or high-severity cases\n \n Collaborate with the Safeguards Policy Design Team on policy gaps surfaced through real enforcement scenarios\n \n Partner with Engineering and Data Science teams to ensure tooling and measurement support enforcement operations.\n \n Keep up to date with emerging AI policy enforcement best practices, threat actor tactics, and the evolving cyber threat landscape, using these to inform enforcement decisions\n \n Minimum qualifications\n \n \n Experience as a people manager\n \n Experience in cybersecurity, including knowledge of offensive techniques, exploit development, malware analysis, or vulnerability research\n \n Experience performing content review, abuse investigations, or policy enforcement at volume\n \n Proficiency in SQL and/or Python for data analysis and threat detection\n \n Experience identifying emerging risks and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams\n \n Experience working with generative AI products, including writing effective prompts for content review and enforcement\n \n Preferred qualifications\n \n \n Experience in trust \u0026 safety, abuse investigations, cybersecurity investigations, or threat intelligence in a technology or AI company\n \n Experience with large language models and an understanding of how AI technology could be misused for cyber operations\n \n Experience operating within abuse monitoring programs or enforcement review systems\n \n Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space\n \n Experience working with government agencies, regulated environments, or information sharing communities\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $285,000 — $330,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit a","salary_min":285000,"salary_max":330000,"location":"Washington, DC","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["security","llm","alignment","generative-ai","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5403775008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-29T02:52:00Z","expires_at":"2026-09-29T13:30:33.098723Z","created_at":"2026-08-29T13:30:34.116902Z","updated_at":"2026-08-30T13:30:33.242494Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4ab10eb7-b0f8-4543-87e5-430128653c2a"},{"id":"ac9a7cfe-0d87-46a1-9a22-dc3d0f92e813","company_id":"12105b3e-eb1d-4a92-95b6-855042facaf1","title":"Senior Product Manager - Core AI (Understand)","slug":"senior-product-manager-core-ai-understand-795d69c4","description":"At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.\n When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.\n Senior Product Manager, Core AI (Understand) \n Why We Have This Role \n \n Define the future of Qualtrics' Understand layer — the intelligence that turns raw experience data into structured meaning, prediction, and insight across the entire portfolio.\n Own the product strategy for the capabilities that let AI systems and product teams reason about experience data: ontologies and semantic systems, text analytics enrichments, prediction, simulation, and benchmarking.\n Own the Core AI platform foundations that these capabilities depend on: agent infrastructure, context and memory, tools and orchestration, agent evaluation, observability, and AI safety.\n Manage the entire lifecycle for multiple functional areas of Understand, from framing the problem, to aligning on architecture and product direction, to forming the plan, delivering implementation, and iterating until the capabilities are world-class.\n \n How You'll Find Success \n \n Partner with product, engineering, data science, research, and design teams across Qualtrics to understand what enrichment, modeling, and platform capabilities they need to build exceptional AI products.\n Develop a deep understanding of the needs of both enterprise customers and internal AI product builders, and translate those needs into strategy, requirements, and roadmaps.\n Define product strategy across the Understand surface area: ontologies and semantic layers, text analytics and enrichment pipelines, predictive models, simulation, benchmarking, and the agent runtime, orchestration, memory, evaluation, and guardrail capabilities that support them.\n Prioritize investments based on customer value, insight quality, developer productivity, technical leverage, reuse across Qualtrics products, and opportunities for competitive differentiation.\n Collaborate deeply with engineering, AI research, and data science teams to make thoughtful product and architectural tradeoffs in a rapidly evolving technical landscape.\n Develop clear frameworks for evaluating the quality, accuracy, reliability, safety, and business impact of enrichment models, predictive systems, and agentic AI.\n Build the benchmarking discipline that lets Qualtrics prove its models and enrichments are better than alternatives — internally and to customers.\n Create shared capabilities that accelerate AI development across Qualtrics while providing the reliability, governance, security, and observability required by enterprise customers.\n Develop and communicate a compelling vision and roadmap to senior leaders, product teams, technical stakeholders, and customers.\n Define and monitor meaningful KPIs for adoption, model and enrichment quality, prediction accuracy, evaluation performance, developer velocity, reliability, and customer impact.\n Stay at the forefront of developments in foundation models, agents, evaluation methods, semantic systems, causal and predictive modeling, simulation, and enterprise AI infrastructure — and translate them into concrete product opportunities.\n \n How You'll Grow \n \n By shaping the technical and product foundations for how Qualtrics understands experience data.\n Through developing deep expertise across ontologies, semantic systems, text analytics, prediction, simulation, benchmarking, agent architecture, and evaluation.\n By making high-leverage product decisions that influence multiple product lines and teams.\n Through leading complex, ambiguous initiatives that require alignment across product, engineering, research, data science, security, and go-to-market organizations.\n By developing your ability to connect rapidly evolving AI technologies to durable customer value and differentiated product strategy.\n \n Things You'll Do \n \n Develop and execute the product strategy for Qualtrics' Understand layer.\n Define the foundational architecture and capabilities required for teams across Qualtrics to build reliable, differentiat","salary_min":166500,"salary_max":218500,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","generative-ai","nlp","alignment","healthcare"],"apply_url":"https://www.qualtrics.com/careers/us/en/job/8164973?gh_jid=8164973","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T21:33:55Z","expires_at":"2026-09-29T13:49:13.602802Z","created_at":"2026-08-29T13:50:43.963199Z","updated_at":"2026-08-30T13:49:13.735129Z","company_name":"Qualtrics","company_slug":"qualtrics","company_logo_url":"https://www.google.com/s2/favicons?domain=qualtrics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ac9a7cfe-0d87-46a1-9a22-dc3d0f92e813"},{"id":"e1618a18-e64a-423b-82d5-022f365f7715","company_id":"df455adb-5b5f-43b9-a3bf-eb48405d2b7b","title":"Software Engineer, Applied AI Research","slug":"software-engineer-applied-ai-research-229b4f6a","description":"About Hightouch\n Hightouch is an Agentic Marketing Platform powered by the industry-leading Composable CDP. With complete brand context, customer data, and performance history in one place, every marketer finally has the power to build and ship end-to-end campaigns themselves. Teams move faster, stay on brand, and get AI marketing that actually works.\n Founded in 2019 and headquartered in San Francisco, Hightouch enables marketing teams to analyze performance, brainstorm ideas, and generate creative at a speed and quality that wasn't previously possible.\n Named a Leader in the 2026 Gartner® Magic Quadrant™ for Customer Data Platforms, Hightouch is trusted by leading enterprises like Domino's, Spotify, Aritzia, Cars.com, Ramp, and PetSmart.\n At Hightouch, our mission is to help our customers leverage data and AI to grow their businesses. The team is ambitious, impact-driven, efficient — and we believe humility, kindness, and compassion are essential to our success. If you're energized by velocity, obsessed with raising the bar, and want to build alongside people who care deeply about each other and our customers, we'd love to meet you.\n About the Role \n We’re looking to add  applied AI research engineers  to the team. The ideal candidate will have strong probabilistic and quantitative thinking, the ability to be highly creative and experimental with LLM applications, and ground their work in potential customer and product applications.\n Our applied research team focuses on finding new and innovative techniques to improve the frontier of what is possible in agentic AI marketing applications, with a particular focus on image and video. We focus less on theory or writing research papers, and more on experimenting, prototyping, and exploring new methods for applying generative AI to help our customers grow their companies.\n Example workstreams include:\n \n Quickly iterating and developing proofs of concept (POCs) to explore the maximum potential of integrating AI into data and marketing workflows\n Design and develop evaluation and improvement systems that can make advancements autonomously\n Expanding the frontier of what is feasible with AI generated video (e.g. making generated humans maximally realistic)\n Experiment with different approaches for generating brand assets that stay aligned to a particular company’s look and feel\n \n We're seeking talented, intellectually curious, and motivated individuals interested in exploring the forefront of AI. While no prior experience with LLMs and AI is required, strong technical skills, particularly in backend architecture or probabilistic systems, and product intuition are essential for understanding and executing these projects from start to finish.\n This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000 - $400,000 USD per year, which is location independent in accordance with our remote-first policy.\n Interview Process\n Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense and creativity with LLMs, ability to architect backend systems, and alignment with Hightouch’s values. Notably, we don’t do any programming interviews as we believe they are low signal to noise and aren’t a good evaluation mechanism.\n \n Recruiter Screen [30m]:  Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit.\n System Design Screen [60m]:  Designing a data processing or machine learning feature end-to-end (depending on background).\n Hiring Manager Interview [30m]:  Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.\n Agent Building Systems Interview [75m]:  Work with the interviewer to architect an agentic system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.\n \n \n E-Verify Statement \n Hightouch participates in E-Verify. After you join the team, we'll verify your eligibility to work in the U.S. by submitting information from your Form I-9 to the Social Security Administration and, if needed, the Department of Homeland Security. This process happens post-hire only — we never use E-Verify to pre-screen applicants. \n E-Verify Notice E-Verify Notice (Spanish) Right to Work Notice Right to Work Notice (Spanish)","salary_min":180000,"salary_max":400000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["llm","agents","generative-ai","search","research"],"apply_url":"https://job-boards.greenhouse.io/hightouch/jobs/6174215004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T21:18:55Z","expires_at":"2026-09-29T13:38:07.054305Z","created_at":"2026-08-29T13:38:40.813703Z","updated_at":"2026-08-30T13:38:07.189907Z","company_name":"Hightouch","company_slug":"hightouch","company_logo_url":"https://www.google.com/s2/favicons?domain=hightouch.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e1618a18-e64a-423b-82d5-022f365f7715"},{"id":"17669270-764c-4f80-a496-6cf3009fcf77","company_id":"a0000000-0000-0000-0000-000000000009","title":"Forward Deployed Engineer, Infrastructure Specialist (Public Sector)","slug":"forward-deployed-engineer-infrastructure-specialist-public-sector-4cfcc1d7","description":"Who are we?\n\nCohere is the leading security-first enterprise AI company.  We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.\n\nWe’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.\n\nWe obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.\n\nWe are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!\n\n\n\n\nABOUT NORTH:\n\nNorth https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.\n\n\n\n\nWHY THIS ROLE?\n\nCohere’s team partners with Canadian public sector organisations to unlock transformative value through secure, ethical deployment of Generative AI (GenAI) solutions. We work collaboratively to address complex societal challenges while maintaining the highest standards of data security and compliance. You will work directly with public sector customers to quickly understand their greatest problems and design and implement solutions using Cohere's stack.\n\nThis role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors.\n\nWe are seeking engineers with diverse skill sets, including backend, infrastructure, agent development, and deployments, who deeply care about customers and want to work at the cutting edge of Agentic AI.\n\n\n\nLocation: Ottawa, 20-40% travel anticipated.\n\n\nSecurity Clearance: Active Top Secret clearance strongly preferred; candidates eligible and willing to obtain clearance will also be considered. If you are ineligible for clearance there are other positions on our careers site that do not have this requirement.\n\nMore information about Canadian Security Clearance can be found here https://www.canada.ca/en/public-services-procurement/services/industrial-security/security-requirements-contracting/personnel-security-screening/processes/security-clearance-request.html.\n\n\n\nIn this role, you will:\n\n -  Lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rollout.\n\n - Partner with enterprise IT teams to assess infrastructure, security requirements, and data management practices.\n\n - Experiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectations\n\n - Design and implement deployment strategies tailored to client needs, ensuring compliance with data privacy and security standards.\n\n - Troubleshoot and resolve deployment-related technical issues, providing timely solutions to minimize downtime.\n\nYou may be a good fit if:\n\n - You have experience with and enjoy working directly with customers\n\n - You have experience deploying enterprise software in private/hybrid cloud environments\n\n - You have proven experience administering production Kubernetes clusters and expertise with Helm\n\n - Familiarity with DevOps practices, CI/CD pipelines, and tools like Git for version control\n\n - You have strong expertise in cloud infrastructure (Azure, AWS, GCP), networking, and virtualization\n\n - You excel in fast-paced environments and can execute while priorities and objectives are a moving target\n\n - Familiarity with Canadian public sector security and compliance requirements (e.g., data sovereignty, access controls).\n\n\n\nCohere is committed to fair and transparent pay practices. The salary range listed for this role reflects the expected base compensation. Actual compensation offered will be determined by factors such as location, level, job-related knowledge, skills, education, and experience.\n\n - Canada:\n   \n   - For candidates in Canada, the Compensation Range is : $175,000 - $385,000 CAD\n\n\n\n\n\n\nFULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:\n\n - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.\n\n - Full health and dental benefits, including a separate budget for mental health.\n\n - RRSP matching, 401K, Pension Scheme.\n\n - 100% Parental Leave top-up for up to 6 months, for either parent.\n\n - Annual enrich","salary_min":175000,"salary_max":385000,"location":"Ottawa","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","payments","cloud","generative-ai","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/cohere/52a2b83b-7537-4e88-af7b-e4e9630a96e0/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T20:35:23.101Z","expires_at":"2026-09-29T13:31:55.712365Z","created_at":"2026-04-30T05:46:56.273345Z","updated_at":"2026-08-30T13:31:55.852872Z","company_name":"Cohere","company_slug":"cohere","company_logo_url":"https://www.google.com/s2/favicons?domain=cohere.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/17669270-764c-4f80-a496-6cf3009fcf77"},{"id":"8f5683c8-4601-44f3-ae28-99878029e10f","company_id":"a0000000-0000-0000-0000-000000000001","title":"Head of Policy Design, Societal Harms","slug":"head-of-policy-design-societal-harms-25b5c82a","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n Anthropic's Safeguards organization builds the policies, evaluations, and detection and enforcement systems that define and hold the limits on how Claude can be used. In this role, you'll lead our policy design team, managing the teams responsible for radicalization, child safety, user well-being, harmful manipulation, and election integrity, among other harm areas.\n The team is responsible for understanding and defining the risks that come with engaging with Claude, how those risks materialize in the real world, and the mitigations needed to prevent them. As the manager, you'll work with your team to draw the boundaries between what is and is not allowed, then partner with research, product, and engineering to build the right interventions. Mitigating these harms takes the whole stack: the values and judgment trained into the model itself, the policies and detection systems we enforce on top of it, and the interventions we build into our products. More capable models, new product surfaces, and new user behaviors will keep testing these boundaries, so the team's policies have to keep pace.\n You'll work closely with product to develop and iterate on the strategy and vision for how our safety layers fit together, and with your team and cross-functional partners to decide which mitigations make the most sense and how to implement them. You'll also coordinate policy decisions across the portfolio: ensuring they're made with the right stakeholders in the room, tracked over time, and applied consistently across harm areas and product surfaces.\n This is a leadership role for someone who combines expertise in the harm areas themselves with fluency in how frontier models are actually developed and deployed, and who does their best work across team boundaries. You'll spend as much time developing the leads who own each harm area as you will on the policy questions themselves.\n *Important context for this role: some of the work involves exposure to explicit content, including material of a sexual, violent, or psychologically disturbing nature.\n Key responsibilities \n \n \n Lead, develop, and grow the managers and teams responsible for the consumer harms portfolio, including child safety, user well-being, harmful manipulation, and election integrity\n \n Coordinate policy decisions across the portfolio, and build the mechanisms that keep them tracked, consistent, and legible — so stakeholders know what was decided, why, and who owns what\n \n Set the strategy for how mitigations built on top of the model — policies, detection and enforcement systems, and product interventions — complement what is trained into the model itself, partnering closely with the alignment training team that owns Claude's character\n \n Prioritize across harm areas competing for the same resources, and make those tradeoffs and their rationale clear to leadership\n \n Serve as the escalation point for high-severity and ambiguous consumer harms decisions, including rapid response to emerging risks\n \n Partner with engineering, data science, product, legal, and research across the model development cycle so consumer harms considerations are represented from training through launch, on every surface where Claude is deployed\n \n Engage external experts, civil society organizations, and regulators, and translate that engagement into stronger policy and enforcement\n \n Minimum qualifications \n \n \n Experience leading teams — including managing managers or senior specialists — in AI safety, product policy, or a related field\n \n Deep, applied familiarity with consumer harm areas such as child safety, mental health and well-being, manipulation, or election integrity, and good judgment about how these harms differ in mechanism, severity, and mitigation\n \n A track record of exceptional cross-team collaboration: building durable working relationships with teams you don't control, and getting to shared decisions where ownership is genuinely distributed\n \n Working understanding of how frontier models are developed and deployed — the training and fine-tuning cycle, evaluations, and launch processes — and how different model environments (consumer products, APIs, agentic tools) change both risk and the mitigations available\n \n Experience translating policy positions into mechanisms that can be enforced and measured, and communicating the reasoning to technical and non-technical audiences, including executives\n \n Sound judgment in ambiguous, high-consequence decisions, and comfort making a call and escalating appropriately on incomplete information\n \n Preferred qualifications \n \n \n Subject-matter depth in one","salary_min":330000,"salary_max":395000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","agents","llm","alignment","fine-tuning","healthcare","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5407418008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T19:56:10Z","expires_at":"2026-09-29T13:30:21.361128Z","created_at":"2026-08-29T13:30:22.347939Z","updated_at":"2026-08-30T13:30:21.508142Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8f5683c8-4601-44f3-ae28-99878029e10f"},{"id":"55f8d3f4-58f6-4ca2-9b49-1e84deeaec13","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Triage Automation Engineer","slug":"triage-automation-engineer-90734211","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role  \n As a Triage Automation Engineer at Wayve , you'll play a key role in scaling our Triage and Detectives workflow through process improvement, tooling, and automation. You'll partner with Triage Specialists and Detective Engineers to turn repeated, manual analysis into reliable, productised automation, including triage bots, behavioural classifiers, and workflow tooling. That reduces manual load and speeds up how quickly we identify, understand, and resolve issues across our test and on-road fleets.\n This is a highly collaborative, detail-oriented role with a direct impact on the safety and efficiency of Wayve's development pipeline.\n Key responsibilities:\n \n Document and measure existing Triage and Detective workflows to identify opportunities for automation and process improvement\n Prioritise improvements based on cost, benefit, impact, and feasibility\n Partner with Detective Engineers to integrate their scripts and tools into scalable, productised workflows\n Work with development, ML, and AI teams to deliver the tooling improvements Triage needs\n Build automation pipelines — including triage bots and behavioural classifiers — that reduce manual load on Triage Specialists\n Validate automation changes and outputs, including the accuracy and reliability of classifications and suggested root causes\n Document newly implemented automations: what they do, how they work, how to use them, known limitations, and expected outputs\n Measure and report on triage quality and throughput to track the impact of automation\n Collaborate with senior management and cross-functional stakeholders to shape the roadmap for business-critical automation\n Willingness to travel domestically and internationally (including trips to our London office)\n \n About you   \n In order to set you up for success as a Triage Automation Engineer at Wayve, we’re looking for the following skills and experience.  \n Essential \n \n 3+ years of experience working with complex systems, ideally within robotics or autonomous vehicles\n Strong scripting and analytical skills (e.g. Python, SQL, Bash/Shell)\n Hands-on experience operating in a remote Linux environment\n Experience building or maintaining data pipelines or notebooks (e.g. Databricks, Jupyter)\n Great communication skills, able to explain complex technical problems to both technical and non-technical stakeholders\n Expertise using issue tracking and configuration management tools such as Jira, Confluence, and Bitbucket/GitLab\n Comfort with ambiguity — able to measure an existing workflow, identify where automation adds value, and scope a sensible solution\n \n Desirable \n \n Experience with web development languages (e.g. HTML, CSS, React, Java) for building internal tooling\n Practical experience with machine learning or classification models (e.g. PyTorch)\n Experience with cloud services (ideally Microsoft Azure)\n Passion for taking research ideas to production\n Track record of promoting statistical rigour and experimental best practice\n Experience working in a fast-moving tech company or startup\n \n This is a full-time role based in our office in Sunnyvale.  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. The reasonably estimated salary for this role ranges from $144,500–$183,200, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.\n  \n Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. \n We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it t","salary_min":144500,"salary_max":183200,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["autonomous-vehicles","generative-ai","robotics","data-pipeline","pytorch","evaluation"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8756182002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T17:56:55Z","expires_at":"2026-09-29T13:43:31.521698Z","created_at":"2026-08-29T13:44:35.170073Z","updated_at":"2026-08-30T13:43:31.651707Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/55f8d3f4-58f6-4ca2-9b49-1e84deeaec13"},{"id":"a9304478-6b78-4ca2-a86c-1622c0c977f2","company_id":"654d4532-88db-435d-8a6f-161b8c5a491e","title":"Senior Manager, Data Science - Styling Algorithms","slug":"senior-manager-data-science-styling-algorithms-ed2bd7cb","description":"About Stitch Fix, Inc. \n Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours.  We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.\n About the Role \n At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems.  \n We are looking for an experienced Styling Algorithms Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our styling algorithms, which empower our human stylists to delight clients by nailing their fit and style. This includes ML-, AI-, and product-driven feature curation and testing for our proprietary styling platform, as well as client-facing AI personalization experiences, such as Stitch Fix Vision, our virtual try-on.\n Responsibilities: \n \n Champion bold AI and ML interventions to improve our styling experiences, enabling our stylists to have a multiplicative impact on their client connection points.\n Likewise, actively shape the product roadmap for direct client-facing styling experiences, expanding the breadth and depth of personalization touchpoints to complement and inform our human stylists.\n Inspire your team by fostering a culture of ideation, ownership, feedback, and collaboration between team members and with cross-functional partners.\n Act as an advocate for our Styling and Merchandising teams, empowering partners to understand trends in stylist feedback and inventory surfacing algorithms for rapid action on emergent opportunities. \n Work with product managers, other data science teams, UI/UX designers, and business leaders to define and optimize against business objectives for our suite of styling experiences.\n Oversee the end-to-end algorithm development lifecycle, from ideation and experimentation to testing and deployment in a production environment.\n Identify and implement best practices for team collaboration, code quality, use of AI, and data management.\n Stay up-to-date with advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.\n \n About You \n This is what you’ll need to succeed in this role from day 1. \n Requirements: \n \n Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s or PhD preferred. \n 5+ years of experience in design and deployment of AI and ML solutions, ideally in retail personalization, with an emphasis on agentic capabilities.\n 2+ years of experience as a team technical lead or direct people manager.\n Ability to write and review production-grade code, ideally in Python.\n Applied knowledge of AI-assisted coding best practices and development of agentic product solutions.\n Excels at building trust with your team, stakeholders, and technical partners.\n Excellent communication skills with the ability to articulate complex technical concepts to business audiences.\n Experience with online A/B testing, experimentation frameworks, and performance metrics.\n Familiar with cloud-based infrastructure and distributed data systems.\n Compensation and Benefits This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site. \n Salary Range\n $200,000 — $246,000 USD \n This link leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts","salary_min":200000,"salary_max":246000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["generative-ai","payments","healthcare","agents","data-science"],"apply_url":"https://www.stitchfix.com/careers/jobs?gh_jid=8164607\u0026gh_jid=8164607","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T16:49:32Z","expires_at":"2026-09-29T13:49:16.042671Z","created_at":"2026-08-29T13:50:46.465007Z","updated_at":"2026-08-30T13:49:16.172549Z","company_name":"Stitch Fix","company_slug":"stitch-fix","company_logo_url":"https://www.google.com/s2/favicons?domain=stitchfix.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a9304478-6b78-4ca2-a86c-1622c0c977f2"},{"id":"57b56d5b-e1f9-4118-afb8-2bd1f37d7f46","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Sr. AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector","slug":"sr-ai-engineer-fde-forward-deployed-engineer-us-federal-sector-2b0534c9","description":"PLEASE NOTE : Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply. \n The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.\n The impact you will have: \n \n Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems\n Own production rollouts of consumer and internally facing GenAI applications\n Serve as a trusted technical advisor to customers across a variety of domains\n Present at conferences such as Data + AI Summit , recognized as a thought leader internally and externally\n Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap \n \n What we look for: \n \n Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy\n Expertise in deploying production-grade GenAI applications, including evaluation and optimizations \n Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.\n Experience building production-grade machine learning deployments on AWS, Azure, or GCP\n Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience\n Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike\n Passion for collaboration, life-long learning, and driving business value through AI\n [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets\n Willing to travel once every 4-8 weeks to see customers (as needed)\n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Local Pay Range\n $182,000 — $250,208 USD \n About Databricks \n Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT\u0026T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affili","salary_min":182000,"salary_max":250208,"location":"Washington, DC","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","data-pipeline","fine-tuning","llm","generative-ai","agents"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8760168002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T14:56:34Z","expires_at":"2026-09-29T13:32:32.139503Z","created_at":"2026-08-29T13:32:27.824973Z","updated_at":"2026-08-30T13:32:32.280262Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/57b56d5b-e1f9-4118-afb8-2bd1f37d7f46"},{"id":"11b73365-9170-4b94-a834-6cf9ce41c2db","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Sr. AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector","slug":"sr-ai-engineer-fde-forward-deployed-engineer-us-federal-sector-3fa2b5eb","description":"PLEASE NOTE : Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply. \n The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.\n The impact you will have: \n \n Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems\n Own production rollouts of consumer and internally facing GenAI applications\n Serve as a trusted technical advisor to customers across a variety of domains\n Present at conferences such as Data + AI Summit , recognized as a thought leader internally and externally\n Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap \n \n What we look for: \n \n Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy\n Expertise in deploying production-grade GenAI applications, including evaluation and optimizations \n Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.\n Experience building production-grade machine learning deployments on AWS, Azure, or GCP\n Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience\n Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike\n Passion for collaboration, life-long learning, and driving business value through AI\n [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets\n Willing to travel once every 4-8 weeks to see customers (as needed)\n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Local Pay Range\n $182,000 — $250,208 USD \n About Databricks \n Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT\u0026T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affili","salary_min":182000,"salary_max":250208,"location":"Virginia","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","fine-tuning","data-pipeline","agents","llm","generative-ai"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8760167002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T14:56:31Z","expires_at":"2026-09-29T13:32:32.232912Z","created_at":"2026-08-29T13:32:27.639904Z","updated_at":"2026-08-30T13:32:32.374987Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/11b73365-9170-4b94-a834-6cf9ce41c2db"},{"id":"0da6da6c-77b3-4ba4-97ca-4eb47129b83d","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Senior Data Scientist, Ads Integrity","slug":"senior-data-scientist-ads-integrity-254eca52","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City \u0026 Chicago) our doors are open for you to come into the office as often as you'd like.\n Reddit is poised to innovate and grow like never before, and Safety is a critical accelerant of that growth. The Safety org is Reddit’s central Trust \u0026 Safety organization, protecting users from bad experiences by stopping harmful content, behaviors, and abuse across the platform. We are looking for a Senior Data Scientist to lead ads fraud detection and scaled enforcement within Safety. You will partner closely with Ads Product, Engineering, Machine Learning, Operations, Policy, Legal, and fellow Safety data scientists to identify emerging ads fraud, define rigorous measurement and evaluation standards, and turn investigations into durable signals, models, rules, and enforcement pipelines. This is a high-impact role with exceptional opportunity for ownership and growth: as an early leader in a greenfield space, you will help define the strategy, shape cross-functional roadmaps, build foundational capabilities, and expand your scope as Reddit’s ads integrity program matures.\n Responsibilities\n \n Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks that make performance measurable and defensible.\n Analyze large, complex datasets and networks of behavior to uncover emerging fraud patterns, size their impact, identify root causes, and translate findings into detection and enforcement requirements.\n Design and develop scalable ads fraud detection and enforcement pipelines in partnership with Engineering and Machine Learning, including feature generation, rules and models, near-real-time scoring, actioning, review feedback loops, and observability.\n Own the full detection lifecycle: backtesting, threshold calibration, offline and online evaluation, launch validation, experimentation, monitoring, drift detection, incident response, rollback, and retirement.\n Build and maintain statistical, machine learning, and GenAI-enabled models or prototypes that improve fraud detection, risk identification, investigator efficiency, and enforcement quality.\n Balance fraud loss, platform and advertiser risk, customer experience, false-positive costs, operational capacity, and business goals when recommending detection thresholds and enforcement strategies.\n Partner across Ads and Safety to shape strategy and roadmaps, strengthen data foundations, close policy and enforcement gaps, and ensure solutions meet governance and compliance standards.\n Translate complex analyses into clear narratives and actionable recommendations for technical and non-technical stakeholders, including senior leaders, and mentor other data scientists and analysts.\n \n Qualifications\n \n Relevant experience in Data Science, Applied Science, or a related quantitative role, preferably in ads fraud, financial fraud, or account risk, Trust \u0026 Safety, platform integrity, or enforcement engineering.\n Ph.D. or M.S. degree in Statistics, Economics, Computer Science, Applied Mathematics, or another quantitative field; with an M.S., 4+ years of industry data science experience, or with a Ph.D., 2+ years of industry data science experience.\n Demonstrated experience building or materially shaping production detection and automated enforcement pipelines, including batch or streaming data, feature engineering, rules or models, decisioning, monitoring, and feedback loops.\n Strong command of fraud or abuse detection methods and evaluation, including label design, precision and recall tradeoffs, calibration, threshold selection, false-positive analysis, drift detection, and adversarial adaptation.\n Experience partnering closely with Product and Engineering teams to translate analyses and prototypes into reliable production systems; experience working across Ads, Safety, fraud, risk, or platform-integrity organizations is preferred.\n Experience applying AI and large language models (LLMs) to practical data science workflows, such as threat discovery, content classification, signal development, investigation automation, or detection and enforcement systems.\n Deep understanding of complex behavioral networks or large-scale activity patterns; experience with methods such as graph or network analysis, clustering","salary_min":190800,"salary_max":267100,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["generative-ai","nlp","healthcare","llm","data-science"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8157580","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T20:49:14Z","expires_at":"2026-09-29T13:38:57.712667Z","created_at":"2026-08-29T13:39:34.881738Z","updated_at":"2026-08-30T13:38:57.847667Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0da6da6c-77b3-4ba4-97ca-4eb47129b83d"},{"id":"bd52fe7c-5d97-4e82-bec6-4431216e869e","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Senior/Staff FDE - Synthetic Data Generation","slug":"seniorstaff-fde-synthetic-data-generation-9477fabd","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n \n About the Role\n Snorkel AI is hiring a Forward Deployed Engineer focused on Synthetic Data Generation to partner with leading AI labs and enterprises on their most critical AI initiatives.\n In this role, you will lead the technical execution of complex customer engagements where synthetic data is used to improve model training, evaluation, and performance. You will translate ambiguous model and data challenges into effective data strategies, build scalable generation and evaluation pipelines, and use experimentation to continuously improve data quality and downstream model outcomes.\n You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements.\n Main Responsibilities\n Synthetic Data Generation \u0026 Evaluation\n \n Design and build scalable synthetic data generation, transformation, filtering, and evaluation pipelines for complex AI use cases\n Translate model objectives, failure modes, and data gaps into synthetic data strategies, experiments, and technical specifications\n Develop LLM- and ML-assisted workflows to generate high-quality training and evaluation datasets across targeted behaviors, domains, and edge cases\n Build automated evaluators, quality checks, and measurement frameworks to assess correctness, relevance, diversity, coverage, and adherence to customer requirements\n Design and run experiments to measure the impact of synthetic data on downstream model performance and iteratively improve generation approaches\n Package and deliver production-grade datasets with standardized formats, quality assurance, and clear documentation\n \n Forward Deployed Engineering \u0026 Customer Partnership\n \n Lead technical workstreams from initial solution design through production delivery, navigating ambiguity and making sound technical decisions\n Build, refine, and iterate on solutions that address customer needs, incorporating feedback to ensure the delivered work provides tangible value\n Rapidly prototype and productionize solutions across models, data pipelines, APIs, and custom applications\n Communicate technical tradeoffs, experimental results, and recommendations clearly to technical and cross-functional stakeholders\n Serve as a trusted technical partner to customers and internal delivery teams, resolving complex blockers and driving alignment\n \n Technical Leadership \u0026 Scale\n \n Identify recurring patterns across customer engagements and turn successful solutions into reusable pipelines, evaluators, tooling, and best practices\n Define and improve technical standards for synthetic data generation, experimentation, evaluation, and delivery\n Partner with DaaS Engineering and Product teams to influence platform and product capabilities based on real-world customer needs\n Lead technical design reviews, share expertise, and provide guidance to other engineers\n Stay current with emerging synthetic data, LLM evaluation, and data curation techniques and assess their applicability to customer problems\n \n What We're Looking For\n \n 5+ years of experience in machine learning engineering, data science, applied AI, forward deployed engineering, or a similar technical role\n Strong Python skills and experience building reliable production data or ML systems, including containerizing with Docker and deploying on cloud platforms (e.g., AWS, GCP, or Azure)\n Hands-on experience with LLMs—building model-based applications and data workflows with the modern GenAI/LLM stack, and integrating systems, models, and data sources through APIs\n Strong understanding of ML experimentation and evaluation, including defining metrics and using empirical results to guide technical decisions\n Experience building synthetic data, data augmentation, or model-generated training and evaluation datasets\n Experience with LLM evaluation techniques, including LLM-as-a-judge, model-based evaluation, rubric-based evaluation, or custom evaluators\n Demonstrated ability to take ambiguous technical probl","salary_min":180000,"salary_max":320000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","llm","reinforcement-learning","agents","generative-ai","fine-tuning"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6167063004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T16:56:44Z","expires_at":"2026-09-29T13:34:01.344588Z","created_at":"2026-08-29T13:34:10.967098Z","updated_at":"2026-08-30T13:34:01.484225Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bd52fe7c-5d97-4e82-bec6-4431216e869e"},{"id":"99ca5606-9232-4b96-8b12-b49baec86bf5","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Senior/Staff FDE - CUA","slug":"seniorstaff-fde-cua-6da3e68e","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n About the Role\n Snorkel AI is hiring a Forward Deployed Engineer focused on Computer Use Agents to partner with leading AI labs and enterprises on their most critical agentic-AI initiatives.\n In this role, you will lead the technical execution of complex customer engagements involving agents that operate computers, browsers, and software environments to complete realistic, multi-step tasks. You will translate ambiguous product and model challenges into robust task environments, datasets, evaluators, and delivery plans that improve agent reliability and downstream performance.\n You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements.\n Main Responsibilities\n Computer Use Agents, Data, and Evaluation\n \n Design and build task environments, datasets, and evaluation workflows for computer-using agents operating across browsers, desktop applications, terminals, and other software interfaces\n Translate customer goals, agent failure modes, and real-world workflows into representative, multi-step tasks with clear success criteria\n Develop data-generation, validation, and quality-assurance pipelines for multimodal and agentic training and evaluation data\n Build automated evaluators, checks, and measurement frameworks to assess task completion, correctness, robustness, efficiency, and adherence to requirements\n Diagnose agent failures across planning, tool use, perception, state management, and interaction with user interfaces; turn findings into improved tasks, data, and evaluations\n Design and run experiments to measure how data, task design, and evaluation changes affect downstream agent performance\n Deliver reusable, production-grade task suites, datasets, and evaluation assets that help customers train, benchmark, and improve computer-use agents\n \n Forward Deployed Engineering \u0026 Customer Partnership\n \n Lead technical workstreams from initial solution design through production delivery, navigating ambiguity and making sound technical decisions\n Build, refine, and iterate on solutions that address customer needs, incorporating feedback to ensure the delivered work provides tangible value\n Rapidly prototype and productionize solutions across models, agent frameworks, APIs, browser or desktop environments, and custom applications\n Communicate technical tradeoffs, experimental results, and recommendations clearly to technical and cross-functional stakeholders\n Serve as a trusted technical partner to customers and internal delivery teams, resolving complex blockers and driving alignment\n \n Technical Leadership \u0026 Scale\n \n Identify recurring patterns across customer engagements and turn successful solutions into reusable task frameworks, evaluators, tooling, and best practices\n Define and improve technical standards for agent task design, environment reliability, evaluation, and delivery\n Partner with DaaS Engineering, Research, and Product teams to influence platform and product capabilities based on real-world customer needs\n Lead technical design reviews, share expertise, and provide guidance to other engineers\n Stay current with emerging agentic-AI, computer-use, evaluation, and data-curation techniques and assess their applicability to customer problems\n \n What We're Looking For\n \n 5+ years of experience in machine learning engineering, software engineering, applied AI, forward deployed engineering, solutions engineering, or a similar technical role\n Strong Python skills and experience building reliable production software, data, or ML systems\n Hands-on experience building, evaluating, or deploying LLM-based or agentic systems, including computer-use agents (CUA)\n Strong understanding of experimentation and evaluation, including LLM-as-a-judge / model-based evaluation, defining metrics, and using empirical results to guide technical decisions\n Experience designing task environments, datasets, and verifiers for agents, including reward \u0026 verifier desi","salary_min":180000,"salary_max":320000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","fine-tuning","reinforcement-learning","data-pipeline","agents","llm"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6167049004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T16:38:34Z","expires_at":"2026-09-29T13:34:01.251345Z","created_at":"2026-08-29T13:34:10.876038Z","updated_at":"2026-08-30T13:34:01.388379Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/99ca5606-9232-4b96-8b12-b49baec86bf5"},{"id":"e82c02c8-1f82-44e8-a6a9-52c07aaa1af9","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Machine Learning Engineer II, Responsible AI","slug":"machine-learning-engineer-ii-responsible-ai-748de33f","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n The Responsible AI team is part of the Advanced Technologies Group (ATG), Pinterest’s advanced machine learning team. ATG’s goal is to keep Pinterest at the forefront of machine learning technology across multiple use cases including recommendations, ranking, content understanding, and more. It is an applied team that works horizontally across the company on state of the art AI and ML and works on directly bringing that technology to the product in collaboration with product engineering teams. The team also publishes its work in applied research conferences, but the main goal of the team is to have a direct impact on business metrics.\n At Pinterest our goal is to inspire pinners (our users) to live the life they love. The product is powered by state of the art ML algorithms which are used to understand both the billions of visually rich items on the platform and the interests of our 535M+ monthly active users and recommend inspiring personalized content to them. What this means is that ML at Pinterest is not only multi-modal utilizing image, text, and graph signals as input, but it needs to operate at a very large scale and often in a real time interactive user experience.\n Pinterest is known for being a positive and inspirational place on the internet and we believe that inspiration begins with representation and belonging. The Responsible AI team is a horizontal team that collaborates across the company on various initiatives. These range from Generative AI alignment, evaluation, and mitigations - ensuring these models are safe, bias-free, and aligned with Pinterest’s vision and policies - to championing ML Fairness and developing user-facing features that enhance our product for all users. This includes launching groundbreaking features such as user-controllable skin tone , hair pattern search refinements, and more recently, body type .\n You’ll help shape forward-thinking projects, develop advanced ML approaches rooted in fairness and equitability, and pioneer responsible AI safeguards for emerging technologies. By joining this team, you’ll make a lasting impact on our Pinners, our business, and the evolution of ethical AI at Pinterest.\n What you'll do: \n \n execute on projects in the responsible AI frontier, to identify, avoid, and mitigate bias across a wide range of ML applications at Pinterest including generative AI. \n Collaborate with other engineering teams (trust and safety, user modeling, content understanding,) to leverage their platforms and signals and work with them to collaborate on the adoption and evaluation of Responsible AI practices and ML Fairness tooling across Pinterest.\n Mentor junior engineers on the Responsible AI team and across the company on the R-AI space.\n Work with the team and senior leaders at the company to define and drive technical strategy in this area.\n \n What we're looking for: \n \n Extensive, real-world experience applying advanced ML methods to production systems, with a strong track record in responsible technology - spanning fairness, ethics, and broader societal considerations.\n Deep familiarity with cutting-edge ML architectures (e.g., transformer-based models, 2-tower architectures, LLMs) and their applications in large-scale Search and Recommender Systems.\n Proven ability to measure, deploy, and refine fairness interventions and broader Responsible AI solutions at scale, bridging state-of-the-art research with tangible product impact.\n 2+ years working experience in the engineering teams that build large-scale ML-driven user-facing products\n Masters or PhD in Comp Sci or related fields\n \n Nice to have: \n \n Publications at top ML conferences\n Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring\n Familiarity with LLM-powered productivity tools for","salary_min":138905,"salary_max":285982,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["generative-ai","code-generation","fine-tuning","llm","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8162046","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T16:29:11Z","expires_at":"2026-09-29T13:38:53.169272Z","created_at":"2026-08-29T13:39:28.752933Z","updated_at":"2026-08-30T13:38:53.311845Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e82c02c8-1f82-44e8-a6a9-52c07aaa1af9"},{"id":"0c041284-ced0-4d3e-bc76-8e40c29f632e","company_id":"d8e15a46-b80d-4228-8e7b-34f00357f377","title":"UX \u0026 Front End Engineer, AI ","slug":"ux-front-end-engineer-ai-192b5fbc","description":"Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.\n What is The Role \n \n The Elastic IT team is shifting beyond standard chat interfaces to craft the next frontier of generative and agentic AI experiences. We are looking for an innovative UX Engineer to join our team to bridge the gap between powerful AI capabilities and intuitive, delightful user interfaces that accelerate productivity across the entire organization. \n \n Our ideal candidate is a skilled front-end engineer with hands-on experience designing and building AI user experiences (e.g., streaming text, dynamic prompt workflows, agent reasoning visualizations, and multi-modal interaction patterns). In this role, you will leverage the latest AI technologies and the Elastic Stack (including ESRE, Agent Builder, Workflows and eUI) to build high-performance front-end applications for a suite of internal products and platforms. Driven by a user-centered mindset, you will act as a key collaborator between AI back-end engineers, product managers, and user groups to turn complex AI reasoning into seamless human-AI interactions. By shaping how enterprise users interact with generative AI, you will enable our global workforce while showcasing the boundary-pushing capabilities of Elastic's products. \n \n Are you ready to design and build the interfaces that supercharge enterprise productivity and prove what’s possible with Elastic? Join us to create AI user experiences that turn collective knowledge into instant action, empowering everyone at Elastic to achieve more. \n What You Will Be Doing \n \n \n AI UI/UX Design \u0026 Implementation: Translate complex generative and agentic AI processes into intuitive, responsive, and engaging front-end interfaces. \n \n Front-End Architecture: Design, build, and maintain front-end UI component libraries. These libraries should be scalable, accessible, and reusable and will be created for generative AI interactions. You will use modern frameworks like React and TypeScript. \n \n Human-AI Interaction Patterns: Prototype and implement novel interaction patterns for conversational AI, agent execution visibility (thought logs, tool calls), prompt systems, and rich dynamic outputs. \n \n Performance \u0026 Streaming Optimization: Optimize UI performance for real-time AI responses, managing token streaming latency, async state management, and optimistic UI updates. \n \n Enterprise Grounding \u0026 Integration: Connect front-end interfaces to internal services. This includes Retrieval Augmented Generation (RAG) endpoints. It also includes Elasticsearch Relevance Engine (ESRE) and agent orchestration APIs. \n \n User-Centered Collaboration: Partner closely with UX designers, product managers, and AI backend engineers to iteratively test and refine AI workflows based on real user feedback. \n \n Accessibility \u0026 Design Systems: Ensure all front-end interfaces strictly adhere to web accessibility standards (WCAG) and align seamlessly with Elastic's core design system (EUI). \n \n AI Observability \u0026 UX Analytics: Implement front-end tracking to monitor user satisfaction, prompt effectiveness , interaction latency, and interface usability. \n \n Documentation: Maintain comprehensive documentation for UI component systems, front-end architecture, and design pattern guidelines. \n \n What You Bring \n \n \n Proven Success in AI UX: Recent experience creating user interfaces for GenAI applications is important. This includes working with conversational interfaces, dynamic prompt builders, and complex agent workflows. \n \n Front-End Mastery: Deep expertise in modern TypeScript , JavaScript , React , HTML5, and CSS/Sass, with an emphasis on modular architecture. \n \n State Management \u0026 Streaming: Deep experience managing complex asynchronous UI state, WebSockets, and Server-Sent Events (SSE) for streaming LLM responses. \n \n UX/UI Design Foundations: Proficient background or active practice in user experience design, wireframing, design systems, and rapid prototyping. \n \n An Appetite to Master Elastic: A solid desire to learn and leverage the Elasticsearch Relevance Engine (ESRE) , Elastic UI (EUI), and the broader Elastic ecosystem. \n \n AI Framework \u0026 API Integration: Experience with integrating front-end systems with AI/LLM backend services and orchestration tools (e.g., LangGraph, REST/GraphQL APIs). \n \n Design System Integration: Experience extending and contributing to enterprise design systems ","salary_min":133200,"salary_max":210700,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["rag","api-design","llm","agents","search","generative-ai"],"apply_url":"https://jobs.elastic.co/jobs?gh_jid=8154995\u0026gh_jid=8154995","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T21:40:36Z","expires_at":"2026-09-29T13:39:18.19693Z","created_at":"2026-08-27T13:39:42.154555Z","updated_at":"2026-08-30T13:39:18.372298Z","company_name":"Elastic","company_slug":"elastic","company_logo_url":"https://www.google.com/s2/favicons?domain=www.elastic.co\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0c041284-ced0-4d3e-bc76-8e40c29f632e"},{"id":"a60887bd-18b6-4819-b8ac-a8ce688f7d3f","company_id":"a0000000-0000-0000-0000-000000000003","title":"Machine Learning Research Scientist, Evaluations","slug":"machine-learning-research-scientist-evaluations-47ca5c35","description":"Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities.\n In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models.\n You will: \n \n Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents.  You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA.\n Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities.\n Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them.\n Publish research findings in top-tier AI conferences.\n \n Ideally you’d have: \n \n Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.\n Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.\n Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development.\n Excellent written and verbal communication skills.\n Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals.\n Previous experience in a customer facing role.\n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:\n $180,600 — $225,750 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. \n We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  \n We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. \n We comply with the United States Department of Labor's Pay Transparency provision .  \n PLEASE NOTE: We co","salary_min":180600,"salary_max":225750,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","fine-tuning","generative-ai","reinforcement-learning","search","nlp","llm","evaluation"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4728014005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T18:51:42Z","expires_at":"2026-09-29T13:31:40.355249Z","created_at":"2026-08-27T13:31:38.7307Z","updated_at":"2026-08-30T13:31:40.501539Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a60887bd-18b6-4819-b8ac-a8ce688f7d3f"},{"id":"e17eda01-e317-4c5f-9dae-d8e3404b1b2e","company_id":"ec4a8bb4-3840-4054-8ccd-77e81db037af","title":"Data Scientist/Senior Data Scientist","slug":"data-scientistsenior-data-scientist-565352fb","description":"C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI \n As a member of the C3 AI Data Science team , you will work with some of the largest companies on the planet helping them build the next generation of AI-powered enterprise applications on the C3 AI Platform. You will work directly with data scientists, AI engineers, and subject matter experts to design and deploy AI capabilities that give our customers the information they need to make better decisions and accelerate their digital transformation. You will identify the right AI approaches for each problem and implement them on the C3 AI Platform so they run reliably at enterprise scale.\n Qualified candidates will have deep knowledge of modern AI and ML techniques — including large language models, agentic systems, and classical statistical methods — along with a clear understanding of their limitations and how to adapt them to large-scale production environments. Some travel is expected.\n Note: This is a client-facing position which requires travel. Candidates should have the ability and willingness to travel based on business needs. \n Responsibilities: \n \n Lead the research, design, implementation, and deployment of AI models, agentic solutions, and optimization algorithms for enterprise applications on the C3 AI Platform.\n Partner with C3 AI customers to build and scale their own AI applications on the Platform.\n Contribute to the design and implementation of new AI capabilities within the C3 AI Platform.\n Analyze model performance across enterprise deployments, diagnose issues such as poor recall or false positive rates, and recommend targeted improvements.\n Collaborate with data engineers and subject matter experts from C3 AI and customer teams to source, validate, and correctly leverage new data assets.\n \n Qualifications: \n \n MS or PhD in Computer Science, Electrical Engineering, Statistics,   Operations Research, or a related field.\n Hands-on AI experience spanning generative AI, agentic systems, supervised and unsupervised learning, and classical regression and classification.\n Strong mathematical foundation in linear algebra, calculus, probability, and statistics.\n Experience building and deploying models at scale in distributed or cloud-native environments.\n Ability to drive projects independently and collaborate effectively across technical and non-technical teams.\n Sharp, motivated, and focused on making a real impact.\n Excellent verbal and written communication skills.\n \n Preferred Qualifications: \n \n Proficiency in Python; experience with JavaScript, Java, or Scala is a plus.\n Familiarity with LLM frameworks (e.g., LangChain, LlamaIndex), vector databases, or RAG architectures.\n A portfolio of AI projects (GitHub, publications, or open-source contributions) is a plus.\n C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. \n California Base Pay Range\n $136,000 — $183,000 USD \n C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.","salary_min":136000,"salary_max":183000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","llm","rag","embeddings","agents","data-science"],"apply_url":"https://c3.ai/job-description/8751111002?gh_jid=8751111002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T17:07:29Z","expires_at":"2026-09-29T13:40:09.638586Z","created_at":"2026-08-27T13:40:52.550205Z","updated_at":"2026-08-30T13:40:09.780051Z","company_name":"C3 AI","company_slug":"c3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=c3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e17eda01-e317-4c5f-9dae-d8e3404b1b2e"},{"id":"4c376d37-cd6f-463d-a12e-7f7436246713","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Site Reliability Engineering Manager, Vehicle Software","slug":"site-reliability-engineering-manager-vehicle-software-967fc97f","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role\n As SRE Manager, you'll build the Vehicle Software SRE team from the ground up — defining its charter, hiring its founding engineers, establishing the operating model, and creating the technical strategy that makes reliability a first-class property of the software running on our vehicles.\n You'll work in a production environment unlike most: a globally distributed fleet of autonomous vehicles operating at the intersection of software, hardware, networking, sensors, and the physical world. Failures are often intermittent, hard to reproduce, and distributed across ownership boundaries. You'll move reliability upstream — from reactive field support to prevention through architecture, automation, observability, and disciplined production readiness.\n You'll embed your team within Vehicle Software, partnering with product teams who retain ownership of what they build while your team provides the reliability engineering, standards, and leverage that help them operate fleet-critical software safely at scale. You'll stay hands-on throughout — writing code, reviewing critical designs, and leading the investigations that matter most.\n The systems you help harden will connect Wayve's AI to physical vehicles and underpin the transition from engineering fleets to commercial operations. Few engineering leadership roles offer this combination of zero-to-one team building, deep systems work, and direct influence on the safety and scalability of autonomous mobility.\n  \n Key Responsibilities\n \n Team building \u0026 leadership : Build and lead a new SRE team from the ground up, staying hands-on as a player-coach on the team's most consequential work.\n Reliability strategy: Own technical direction for vehicle software reliability across deployment, service health, telemetry, and diagnostics; define what production-ready means at Wayve.\n Production readiness: Define SLIs, SLOs, and error budgets for fleet-critical workflows; drive release criteria, automated gates, rollback strategies, and fault-injection practices across Vehicle Software.\n Observability \u0026 tooling: Design and implement the observability and automation that shortens the path from vehicle symptom to root cause, cuts the manual toil between failure and fix, and shapes systems for robustness, recoverability, and debuggability.\n Incident response: Lead investigations into complex failures, ensure every incident produces a durable fix, and strengthen on-call practices and escalation paths across service-owning teams.\n Mentorship \u0026 communication: Mentor engineers and emerging leaders, and give senior leadership the clarity on reliability health, risks, and investment they need to make good decisions.\n \n  \n About you\n Essential \n \n 8+ years building and operating production software systems with strong depth in SRE, production engineering, platform engineering, embedded systems, or robotics, and a recent track record of writing production-quality code and leading architecture reviews across Linux-based, distributed, or hardware-software systems.\n 3+ years in people leadership with a track record of hiring, coaching, and growing engineers across levels while staying actively engaged in coding, design, and code review; experience forming a new team or capability from scratch is a strong plus.\n Proven experience with SLOs, error budgets, production-readiness standards, observability, incident management, postmortems, and toil-reduction programmes, with measurable outcomes to show for it.\n A track record of turning ambiguous, cross-functional problems into clear ownership, sequenced plans, and reliable delivery without relying on formal authority.\n Hands-on experience building production software, automation, and diagnostic tooling in C++, Rust, Python, or Go, with familiarity with CI/CD, release systems, telemetry pipelines, and modern observability tooling.\n Calm and structured during incidents, with clear communication across software, hardware, operations","salary_min":276100,"salary_max":311400,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["autonomous-vehicles","generative-ai","robotics","devops"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8728803002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T20:00:30Z","expires_at":"2026-09-29T13:43:28.958489Z","created_at":"2026-08-26T13:43:37.362178Z","updated_at":"2026-08-30T13:43:29.088912Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4c376d37-cd6f-463d-a12e-7f7436246713"},{"id":"385357c5-623e-4db0-baf5-06182c0f554f","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Staff Machine Learning Engineer, Emergency Trajectory Models","slug":"staff-machine-learning-engineer-emergency-trajectory-models-f0038f44","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The role  \n As a Staff Machine Learning Engineer in Wayve's AV Core organization, you will lead the technical direction and delivery of a learned emergency trajectory model for low-frequency, high-consequence maneuvers such as evasive steering and emergency braking. You will take the programme from problem definition through modelling, evaluation, integration, and evidence for deployment.\n Emergency maneuvers are rare, high-consequence events that place unusual demands on data, modelling, and validation. The hard problem is not simply to train another trajectory head: it is to define the operating envelope of a specialist model, what evidence shows that it improves outcomes without introducing new failure modes, and how it integrates with the general driving model and surrounding system. You will lead that work across AV Core and with partners across simulation, evaluation, safety, and product engineering.\n  \n Key responsibilities \n \n Set the technical strategy and roadmap for the emergency trajectory model, including its behavioral scope, operating envelope, system interfaces, and measurable acceptance criteria.\n Design and train trajectory-generating policies using the methods best supported by evidence, including behaviour cloning, reinforcement learning, or other sequential decision-making approaches.\n Build a data strategy for rare emergency cases, combining fleet data, targeted mining, simulation, augmentation, and reweighting while controlling coverage gaps and unintended behavior.\n Create rigorous open-loop and closed-loop evaluations for collision avoidance, evasive steering, emergency braking, recovery, robustness, latency, and regressions in nominal driving.\n Lead integration into the shared driving stack, align technical decisions across teams, and raise the bar through architecture reviews, mentoring, and clear communication of risks, trade-offs, and evidence.\n \n About you   \n In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.  \n  \n Essential  \n \n A track record of staff-level technical leadership: setting direction for ambiguous machine learning programmes, aligning multiple teams, and carrying work from research through production deployment.\n Deep expertise developing learned trajectory-generation or policy models for embodied systems, including architecture design, objective design, training, and empirical validation.\n Hands-on experience with behaviour cloning, reinforcement learning, or related methods, including objective design, distribution shift, robustness, and closed-loop failure analysis.\n Strong machine learning engineering skills in Python and PyTorch, with experience building reproducible training and evaluation systems on large, heterogeneous datasets.\n Exceptional technical judgement and communication: able to make safety-relevant trade-offs explicit, define the evidence needed for decisions, and lead without relying on formal authority.\n \n  \n Desirable  \n \n Experience applying learned models in autonomous driving or robotics, with strong understanding of motion planning, vehicle dynamics, control, or collision avoidance.\n Experience with specialist, fallback, redundant, mixture-of-experts, or model-routing architectures and the interfaces used to select between them.\n Experience mining, generating, or evaluating rare events using simulation and fleet or real-world data.\n Experience deploying learned policies under real-time latency, reliability, and compute constraints; proficiency in C++, CUDA, or systems optimisation.\n Experience with multimodal, transformer-based, diffusion-based, or other generative trajectory or policy models.\n \n This is a full-time role based in our office in Sunnyvale.  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and lear","salary_min":336400,"salary_max":370300,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","gpu","robotics","autonomous-vehicles","generative-ai","pytorch","machine-learning"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8747065002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T18:15:27Z","expires_at":"2026-09-29T13:43:29.618384Z","created_at":"2026-08-25T18:31:14.484268Z","updated_at":"2026-08-30T13:43:29.754954Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/385357c5-623e-4db0-baf5-06182c0f554f"},{"id":"9a42e317-7954-4330-9e7d-59cad3214bb9","company_id":"8115806a-6d9c-48b9-9a92-5eb180bbd1ef","title":"Applied Research Scientist, AI Research","slug":"applied-research-scientist-ai-research-428d0a90","description":"Descript's Research team builds the models behind the product's most distinctive features: Video Regenerate and lipsync, video translation, zero-shot voice and roomtone cloning, and Studio Sound. We don't build general-purpose generative models. We pick specific problems in the editing workflow and build specialized models for them. This isn't research for its own sake. Everything we build is meant to ship, and most of it has, going from prototype to a production feature used by millions of creators within months.\n This role is focused on multimodal understanding: training models to perceive edited media the way a human video editor does. Underlord, our AI editing agent, reasons about a project largely through a textual representation of it. Giving it direct perception of the media it's working on is what will let it judge its own output and reason about the creative choices in an edit, not just the structure of a project. It's also an open research problem, since there's no settled way to represent or evaluate editorial craft, whether a cut lands or whether the pacing works. We have a unique dataset to work with.\n Some recent work from the team:\n \n Audio editing by latent inpainting : regenerating a masked span of speech \n Video Regenerate : regenerating a speaker's lower face to match new or translated audio\n Jumpcut Smoothing : generating a bridge across a cut so the join plays like a continuous take\n Anchored Tree Sampling : tree-based imputation that bounds drift in long video generation\n PoDAR : disentangling power from semantics in audio latents to make them easier to model\n \n More at descript.com/research .\n What you'll do\n \n Multimodal understanding: build vision-language systems that let Descript's agentic editing features reason over the visual and audio content of a project.\n Evaluation: design the benchmarks and evals that make editorial quality measurable, and that balance quality against cost and latency.\n Data: build the datasets your work depends on, including synthetic data generation where real examples don't exist at scale.\n Training: train specialized models from scratch or fine-tune existing foundation models, whichever gets the capability we need.\n Shipping: take models from prototype to production with the agent and engineering teams.\n Direction-setting: identify the next research direction that should become a Descript feature, not just a paper. More senior candidates should expect to own this directly; more junior candidates will grow into it.\n Publishing: take your work to academic venues if you'd like. We support it, but it isn't a requirement of the role.\n \n What you bring\n Required\n \n Proven ability to design and implement deep learning algorithms, demonstrated by publications, open-source work, or models you've shipped.\n Strong programming skills and deep fluency in PyTorch.\n A track record of generating new ideas in machine learning. You produce more ideas than you can implement, and once an experiment setup is established, you can run and evaluate many of them quickly rather than being bottlenecked on infrastructure.\n Strong experimental judgment. You test ideas fast, and you're honest with yourself and the team about which ones don't pan out.\n Clear written and verbal communication, including when a direction isn't working, so the team doesn't waste time following a lead that's already dead.\n A PhD or Master's in deep learning or a related field, or equivalent experience. We care about the track record more than the credential.\n \n At least one of the following must be true:\n \n Lead or first author of an accepted publication in a top venue: CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, or similar.\n Played a key role in shipping a production feature with deep learning as a core component.\n \n More senior candidates (Senior and Staff) should also bring a track record of owning research direction rather than executing a plan handed to them, and experience mentoring or technically leading other researchers or engineers.\n Where breadth helps\n Direct experience in multimodal understanding is welcome but not required, and we don't require domain-specific expertise in computer vision or speech and audio. Our team spans both, and strong general deep learning ability transfers. We hire against the bar above, and then expect you to grow into the domain. Depth in any of these is a strong signal:\n \n Vision-language models and multimodal understanding.\n Generative modeling for video, audio, or images.\n Post-training, fine-tuning, and RL on large foundation models.\n Building evaluation systems for generative or agentic outputs where metrics resist clean definitions.\n Taking a research idea through to a shipped, production-facing feature.\n \n Compensation and benefits\n Base salary range: $197,000–$262,500, plus equity and benefits. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, and level, and may vary from the amount above.\n  \n IMPO","salary_min":197000,"salary_max":262500,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","deep-learning","fine-tuning","computer-vision","pytorch","healthcare","agents","research"],"apply_url":"https://boards.greenhouse.io/descript/jobs/7967440003?gh_jid=7967440003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T00:18:24Z","expires_at":"2026-09-29T13:35:54.489992Z","created_at":"2026-08-25T18:27:44.358668Z","updated_at":"2026-08-30T13:35:54.624927Z","company_name":"Descript","company_slug":"descript","company_logo_url":"https://www.google.com/s2/favicons?domain=descript.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9a42e317-7954-4330-9e7d-59cad3214bb9"}],"page":1,"per_page":20,"total":1608,"total_is_exact":true,"total_pages":81}