{"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":"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":"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":"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":"42d0b3d6-fb09-4db9-9c43-b451572a2005","company_id":"da5cfe83-4fb2-4ab3-9392-94069a77ae59","title":"Staff/Senior Staff Software Engineer, Agentic Search","slug":"senior-staff-software-engineer-agentic-search-c4676bc8","description":"Ironclad is the leading AI contracting platform that transforms agreements into assets. Contracts move faster, insights surface instantly, and agents push work forward, all with you in control.  Whether you’re buying or selling, Ironclad unifies the entire process on one intelligent platform, providing leaders with the visibility they need to stay one step ahead. That’s why the world’s most transformative organizations, from Rivian to the World Health Organization and the Associated Press, trust Ironclad to accelerate their business.\n\n\nWe’re consistently recognized as a leader in the industry: a Leader in the Forrester Wave and Gartner Magic Quadrant for Contract Lifecycle Management, a Fortune Great Place to Work, and one of Fast Company’s Most Innovative Workplaces. Ironclad has also been named to Forbes’ AI 50  and Business Insider’s list of Companies to Bet Your Career On. We’re backed by leading investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton. For more information, visit www.ironcladapp.com http://www.ironcladapp.com or follow us on LinkedIn.\n\n\n\n\nABOUT THE ROLE\n\nIronclad's Intelligence Platform team owns Agent Assistant, Conversational Search, and Content Understanding — the systems that help customers and AI agents understand, find, and act on the right contract information. These are the flagship AI capabilities of our product, built and operated by a combined team of ML and ML infrastructure engineers.\n\nWe have multiple roles open, and are hiring a range of levels — Staff and Senior Staff. As a Staff or Senior Staff Engineer, Agentic Search, you'll own the architecture that combines LLMs and retrieval systems to answer complex, ambiguous questions about a customer's contracts, and you'll set the technical direction that other engineers across the AI organization build on. You'll partner closely with product, applied science, and engineering leaders to raise the company's search quality bar, and you'll bring the technical depth and eval-driven rigor to turn ambiguous problems into shipped, measurable improvements. Scope and ownership will be calibrated to level.\n\n\n\n\nWHAT YOU'LL DO\n\n - Own agentic search architecture. Design and evolve the systems that combine LLMs and retrieval to produce optimal answers to complex or ambiguous questions.\n\n - Drive eval-driven development. Design and run the benchmarks and experiments that measure search quality, and use that feedback to continuously improve the system.\n\n - Raise the search quality bar. Contribute to and influence the company's overall search quality standard.\n\n - Own content understanding and ingestion. Turn raw documents into processed data that retrieval systems can consume, by building and using NLP/LLM models and pipelines.\n\n - Set technical direction. Define architectural decisions and technical direction that other engineers across the AI organization build on.\n\n\nQUALIFICATIONS\n\n - 10+ years building production systems, with a substantial portion in search, information retrieval, content understanding, or recommendation systems at meaningful scale.\n\n - Demonstrated depth in one of: learned/hybrid retrieval (lexical + vector + reranking), query understanding/NLU pipelines, or production LLM agent systems — ideally more than one.\n\n - Experience with search frameworks (Elasticsearch or equivalent — Solr, Vespa, OpenSearch; embedding search) in production, including relevance tuning and reranking.\n\n - Fluency with modern LLM APIs and multi-provider orchestration (Anthropic, OpenAI, Google) — reasoning about token budgets, provider-specific tool-calling semantics, and prompt-caching trade-offs.\n\n - Experience building eval-driven workflows — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hoping.\n\n - Strong autonomy, ownership, and technical leadership across teams, including mentoring senior engineers and driving architectural decisions.\n\n - Comfortable operating in a dynamic, fast-paced, outcome-driven environment.\n\n\nGREAT TO HAVE\n\n - Hands-on experience with post-training algorithms and infrastructure, including SFT and RL.\n\n - Experience with content understanding and/or information retrieval in structured-document-heavy domains.\n\n - Prior work on RAG systems involving data sources in different formats (Google Docs, PDFs, DOCX, etc.).\n\n\n\n\n\nBASE SALARY RANGES\n\n - Staff: $188,000 - $235,000\n\n - Senior Staff: $220,000 - $270,000\n\nThe base salary range represents the minimum and maximum of the salary range for this position based at our San Francisco headquarters. The actual base salary offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our base salary is just one component of Ironclad's competitive total rewards package, which also includes equity awards (a new hire grant, along with opportunities for additional awards throughout ","salary_min":220000,"salary_max":270000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","nlp","rag","agents","search"],"apply_url":"https://jobs.ashbyhq.com/ironcladhq/4be2d35a-9aa0-415c-ba13-30da080158ad/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T20:47:44.879Z","expires_at":"2026-09-29T13:41:24.070143Z","created_at":"2026-08-26T13:41:23.863704Z","updated_at":"2026-08-30T13:41:24.20808Z","company_name":"Ironclad","company_slug":"ironclad","company_logo_url":"https://www.google.com/s2/favicons?domain=ironcladapp.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/42d0b3d6-fb09-4db9-9c43-b451572a2005"},{"id":"d29bfaad-c593-4c53-93b1-dff4b4c64a86","company_id":"adc4981a-d4ff-4939-952f-362f51e1291d","title":"Sr. Machine Learning Engineer","slug":"sr-machine-learning-engineer-3ba58cf5","description":"Our Mission: \n 6sense's mission is to multiply what matters: growth, retention, and efficiency.  We envision a future where companies, teams and people reach their full potential.\n Our People: \n People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging.  Every 6sensor plays a part in defining the future of our industry-leading technology.  6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers.  We want 6sense to be the best chapter of your career. \n \n About 6sense\n 6sense is Intelligence for Agentic GTM. We turn every signal — yours and ours — into intelligence that every team, tool, and AI agent can act on and trust. Every day, the 6sense Signalverse™ captures one trillion signals to power AI that pinpoints who’s ready to buy, how to engage them, and when to act. 6sense was named a Leader in The Forrester Wave™: Revenue Marketing Platforms for B2B, Q1 2026.\n The Opportunity\n We’re hiring a Senior Machine Learning Engineer to join our AI team, reporting directly to the Head of AI.\n Signals tell you what happened. Our job is to explain why — and that is the problem you will work on. You will build the intelligence that turns a trillion daily signals into cited, explainable answers about why an account matters, why now, and who is deciding. Your models power products customers use every day, including RevvyAI, our conversational GTM intelligence product, and reach their stack through our APIs and MCP server.\n This is a build-and-ship role, not a research role. You will own problems end to end, work directly with Product and Go-to-Market, and see your work reach customers. You’ll join a team distributed across the US and India, at a company where AI is the product rather than a feature.\n What You’ll Do\n \n Own machine learning problems end to end — from data exploration and modeling through deployment, monitoring, and iteration in production.\n Build NLP, LLM, and agentic systems at enterprise scale, including retrieval-based architectures and multi-agent workflows.\n Develop ranking, recommendation, prediction, and optimization models that are explainable rather than black-box.\n Partner with Product and Go-to-Market to turn ambiguous business problems into shipped capabilities.\n Improve the performance, scalability, and reliability of production ML systems, and help shape AI platform architecture.\n Explain your work clearly to technical and non-technical audiences, and engage with customers when needed.\n Mentor engineers and raise the bar for engineering excellence.\n \n What We’re Looking For\n Required\n \n 8+ years of industry experience building and deploying machine learning systems in production, with clear end-to-end ownership.\n Strong foundation in machine learning and applied statistics, with hands-on depth in NLP, transformers, embeddings, and retrieval-based systems.\n Practical experience with modern GenAI tooling such as LangGraph, LangChain, or Amazon Bedrock.\n Strong Python skills and experience building distributed ML pipelines on cloud infrastructure (AWS, Databricks, or equivalent).\n Solid grasp of feature engineering, model evaluation, and MLOps practices.\n A product mindset — you want to build AI products customers use, and you measure yourself on customer impact.\n Excellent communication: you can explain complex technical work clearly, tell the story of what you’ve built and why, and hold your own with product and business partners.\n Comfort with ambiguity and the judgment to drive execution independently.\n \n Nice to Have\n \n Experience with RAG architectures, vector databases, and prompt engineering.\n Hands-on work with PyTorch or TensorFlow.\n Background in B2B SaaS, enterprise AI products, or forward-deployed engineering — especially where you worked directly with complex customer data and delivered quickly.\n \n  \n Base Salary Range: $200,349.50 - $260,912.60. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote \n Notice of Collection and Use of Personal Information for California Residents: California Recruitment Privacy Notice and Policy \n Our Benefits:   \n Full-time employees can ta","salary_min":200349,"salary_max":260912,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["tensorflow","nlp","fine-tuning","rag","generative-ai","pytorch","payments","llm"],"apply_url":"https://boards.greenhouse.io/6sense/jobs/8064973?gh_jid=8064973","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T15:47:30Z","expires_at":"2026-09-29T13:41:04.935693Z","created_at":"2026-08-25T18:30:07.718512Z","updated_at":"2026-08-30T13:41:05.080754Z","company_name":"6sense","company_slug":"6sense","company_logo_url":"https://www.google.com/s2/favicons?domain=6sense.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d29bfaad-c593-4c53-93b1-dff4b4c64a86"},{"id":"88c598ce-9fe7-4103-ba06-6a02f5b5f2f2","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Senior ML/AI Modeler, Risk Automation Machine Learning","slug":"senior-mlai-modeler-risk-automation-machine-learning-d62ab6c1","description":"Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.\n The Role \n The Risk Automation ML team automates Risk and Compliance investigations and decision making at Block through the application of agentic and generative AI technology. We work globally with partners in Product, Engineering and Operations to ensure that we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform.\n We are leveraging agentic and generative AI as an integral part of our toolkit to fulfill our mission. Block's machine learning systems monitor billions of payment transactions across traditional payment and blockchain networks and surface suspicious activity (fraudulent, suspicious, illegal activity and brand violations) for trained Operations analyst review and decisioning. We are leveraging generative AI to accelerate historically manually intensive analyst workflows; by adding features in the investigative UX to accelerate agent productivity and enable them to make faster, more informed and accurate decisions (aka Copilots). We also automate workflows end to end completely eliminating the need for manual reviews (aka Autopilots).\n This is a new and significant opportunity to rethink and optimize Risk Operations at Block at scale. This is an IC role, but the senior level has significant leadership responsibilities that include owning, and driving strategic roadmaps \u0026 priorities to completion by collaborating with relevant cross functional stakeholders.\n (Work from anywhere: This role can be performed from any location in the United States and Canada)\n You Will \n \n Experiment and deploy AI copilot and autopilot systems at scale to improve analyst productivity and/or eliminate manual decision loops altogether.\n Own the end to end system including API calls to disparate data sources, advanced prompt tuning, orchestration, metrics and evaluation, productionization and monitoring.\n Leverage diverse data sets that include payment transactions, connected users and asset graphs, unstructured text data and user profile information to build transformer based ML models to improve downstream detection tasks.\n Work cross functionally with product, platform, engineering and operational stakeholders to deploy production grade systems and monitor and tune ongoing performance.\n Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP \u0026 AWS) to get the job done.\n Leverage agentic tools (Claude Code/Codex/Openclaw) to supercharge your research, development, devOps and documentation work as part of your day to day.\n \n You Have \n \n 8+ years of Machine Learning modeling experience. Full stack ML experience is strongly preferred.\n A Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field.\n 3+ yrs experience with AI engineering, Large language models, and a background in traditional NLP techniques is a strong plus for this role.\n End to end experience of building and deploying ML/AI to production systems (batch and real time) that are performant at scale.\n Experience of independently owning, influencing and driving programs with multiple cross functional stakeholders that have significant business impact.\n Have a curious, growth-oriented mindset and the ability to think in first principles to identify creative solutions that demonstrate value.\n \n  \n We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and \"fair chance\" ordinances.\n We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page .\n While there is no specific deadli","salary_min":194500,"salary_max":291700,"location":"San Francisco, CA","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["cloud","payments","llm","agents","generative-ai","nlp","pytorch","code-generation"],"apply_url":"http://block.xyz/careers/jobs/5394441008?gh_jid=5394441008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T18:24:19Z","expires_at":"2026-09-29T13:39:46.526987Z","created_at":"2026-08-25T18:29:18.489401Z","updated_at":"2026-08-30T13:39:46.664819Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/88c598ce-9fe7-4103-ba06-6a02f5b5f2f2"},{"id":"1cad2fe0-dc9a-4db6-b598-e5cb2d7f66b1","company_id":"fb64b18b-041a-43de-886d-f506d1ab94a4","title":"Senior Staff Product Manager, Purple AI","slug":"senior-staff-product-manager-purple-ai-cfe5605e","description":"Our Purpose \n At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.\n About Us \n SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.\n Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.\n What Are We Looking For? \n We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.\n We're looking for an AI-native product manager to join SentinelOne's Purple AI team and lead the vision and execution for next-generation agentic security features. Purple AI is how modern SOC teams detect earlier, respond faster, and stay ahead of attackers—and SentinelOne is embedding it platform-wide to automate security operations while keeping human analysts fully in control and accountable. You'll own the roadmap for new agentic capabilities and drive the evolution of our conversational experience, continually redefining what modern AI in cybersecurity looks like. This is a high-visibility, strategic role with direct exposure to executive leadership and close collaboration across engineering, sales, marketing, and pricing strategy.\n What Will You Do? \n \n Define and champion the strategy and vision for Purple AI—the industry's first GenAI security analyst—along with new AI features driving SentinelOne's next phase of growth\n Own the full product lifecycle, from ideation through launch and iteration, to deliver measurable customer and business impact\n Synthesize quantitative and qualitative inputs—product metrics, user research, and market analysis—to shape the roadmap and build customer-centric solutions\n Make robust decisions amid incomplete, conflicting, or ambiguous information, managing risk and rallying cross-functional teams around a shared path forward\n Refine online and offline evaluation metrics to track with customer-perceived quality and value, and drive our data-sourcing strategy to continuously improve model and pipeline performance\n Partner with marketing, sales, and documentation to craft a compelling product narrative that drives adoption of our AI products\n \n What Skills and Knowledge Will You Bring? \n \n 8+ years in enterprise product management; cybersecurity product experience preferred\n 5+ years building AI/ML products\n 3+ years launching 0-to-1 enterprise software products\n Bachelor's or advanced degree in computer science, data science, or related field (or equivalent experience)\n Strong technical grasp of AI/ML technologies, including generative and agentic AI, natural language processing (NLP), and retrieval-augmented generation (RAG)\n Exceptional skill navigating ambiguity, framing trade-offs, and making decisions that balance technical complexity, user experience, and business value\n Ownership mentality: proven accountability, persistence, and a results-driven mindset\n Clear, efficient, and persuasive communication—written and verbal—across audiences from engineers to executives\n Hands-on experience using AI tools to accelerate the full PM workflow, improving both the speed and quality of decision-making\n \n Note: This position requires up to 15% travel to customer and SentinelOne locations worldwide. \n Why SentinelOne?\n AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.\n We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:\n Equity \u0026 Rewards \n \n Restricted","salary_min":184000,"salary_max":253000,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["nlp","rag","agents","generative-ai","security"],"apply_url":"https://www.sentinelone.com/jobs/?gh_jid=7857160003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T16:53:19Z","expires_at":"2026-09-29T13:49:24.915833Z","created_at":"2026-08-25T18:33:46.361062Z","updated_at":"2026-08-30T13:49:25.047221Z","company_name":"SentinelOne","company_slug":"sentinelone","company_logo_url":"https://www.google.com/s2/favicons?domain=sentinelone.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1cad2fe0-dc9a-4db6-b598-e5cb2d7f66b1"},{"id":"b1638ac7-d1b2-4de0-b991-6d17c0656bb6","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Staff Gen AI Research Scientist ","slug":"staffgenai-research-scientist-f60a2c4a","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM   \n The Air Dominance \u0026 Strike team at Anduril develops aerial and multi-domain robotic systems. The team is responsible for taking products like Fury (unmanned fighter jet) and Barracuda (air-breathing cruise missile) from concept to product. The team also develops Lattice for Mission Autonomy, Anduril’s premier software platform that enables masses of Fury, Barracuda, and other first and third party robots to collaborate across various missions. We work in close coordination with specialist teams like Perception, Motion Planning, Hardware, and Test Engineering to solve some of the hardest problems facing our customers. We are looking for AI research scientists, Applied scientists and roboticists excited about creating a powerful autonomy software stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications.   \n ABOUT THE JOB   \n We are seeking an  AI Research Scientist  to serve as a founding ML expert on our team. In this role, you will design, fine-tune, and deploy the next generation of generative AI, LLMs, and agentic systems that power our air-dominance platforms and collaborative autonomous behaviors.    \n This is a highly applied research role  (split roughly 60% applied research/experimentation and 40% hands-on coding)  focused on making state-of-the-art LLM models smaller, faster, and smarter. You will work on both offboard systems (for complex mission planning, modeling, and simulation) and onboard systems—optimizing models to run directly on power- and compute-constrained edge hardware. As an early member of this initiative, you will have significant autonomy to set the technical direction, design our data collection strategy across test sites and simulations, and directly influence how multi-agent autonomy is deployed in critical missions.   \n WHAT YOU’LL DO   \n \n Develop, pre-train, and fine-tune in-house LLMs and multimodal foundation models. Apply SOTA post-training alignment techniques (SFT, RLHF, DPO) to maximize capability while minimizing cost and footprint. \n Architect and optimize models to run directly on tactical edge compute and power-constrained hardware onboard physical assets. Optimize model latency, memory usage, and execution speed through quantization, distillation, and pruning. \n Design and implement robust agentic architectures, multi-agent coordination frameworks, and planning loops for complex, multi-domain military missions. \n Collaborate closely with computer vision, perception, and motion planning teams to build systems capable of reasoning over diverse modalities, including camera feeds, radar, telemetry, and text-based operational orders. \n Define and execute data collection strategies across physical assets, test sites, and virtual simulations. Work with AI Infrastructure engineers to build scalable evaluation frameworks that measure model performance, reliability, and safety in high-stakes environments. \n Build early-stage prototypes alongside customers, quickly iterate on feedback, and scale those prototypes into production-grade features deployed across our family of systems.   \n \n REQUIRED QUALIFICATIONS   \n \n Strong production-level coding skills in Python and deep learning frameworks (like PyTorch or JAX).  \n Hands-on experience training, fine-tuning, and evaluating LLMs, Generative AI, or multimodal models. \n A strong background in a classical technical discipline (Computer Vision, NLP, Robotics, or Speech) with 2+ years of dedicated experience focusing on generative models and modern transformer architectures. \n Experience using modern model training, alignment, and orchestration tools (e.g., Axolotl, Hugging Face, DeepSpeed, Megatron-LM, LangChain, or LlamaIndex). \n Ability to operate comfortably in a fast-paced environment, moving from ambiguous mission requirements to concrete code and functional prototypes. \n Degree (B.S., M.S., or Ph.D.) in Computer Science, Machine Learning, Robotics, Physics, Mathematics, or a related technical field. \n Eligible to obtain and maintain an active U.S. Top Secret security clearance.   \n \n PREFERRED QUALIFICATIONS   \n \n Proven track record of compiling and running deep learning models on edge accelerato","salary_min":220000,"salary_max":292000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","cloud","payments","robotics","diffusion-models","generative-ai","pytorch","nlp"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5216230007?gh_jid=5216230007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T16:20:23Z","expires_at":"2026-09-29T13:37:30.58848Z","created_at":"2026-08-25T18:28:19.681085Z","updated_at":"2026-08-30T13:37:30.721438Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b1638ac7-d1b2-4de0-b991-6d17c0656bb6"},{"id":"870c8dc8-5777-448d-8df3-6185edbad22d","company_id":"24cd325c-d323-4000-9270-131ae4b3f35a","title":"Director of Robot Applications and Behavior","slug":"director-of-robot-applications-and-behavior-d95e370a","description":"Burro is the leading robotics company in the world by number of robots working outdoors in the field with real customers. Our mission is to free people from tedious work and solve the critical labor shortages faced by farmers and others that work outdoors. \nTo accomplish our mission, we need a world-class, diverse team where everyone feels comfortable sharing their ideas. With this in mind, we strive to create a work environment where every employee can be themselves and express their perspective – this enables us to deliver the most creative and innovative solutions to problems our customers face. \nHeadquartered in Philadelphia with an office in central California, and backed by top Agtech and autonomy investors, including S2G, Catalyst, Translink, Cibus, FPrime, Toyota Ventures, FFVC, Xplorer, and Radicle, Burro was created to solve the labor shortages facing farmers using robotics. \nBurros can be described as Disney's Wall-E for agriculture and work outdoors, in a 1.0 format.  They function, today, as computer vision based autonomous ground vehicles for carrying, towing, and scouting, and are designed to lay the base for the fully autonomous future of work outdoors.  We have 700+  robots in our growing fleet deployed in paid commercial use within vineyards, nurseries, berries, and beyond, and demand for our product is accelerating, so we are growing our team.  \n \nThe Role\nWe are seeking a Director of Robot Applications and Behavior to lead the team that owns what the robot does and how people interact with it: the behavior stack and state machines that sequence a mission, the integration work that gets new behaviors from simulation onto robots in the field, the backend communication between robot and cloud, the operator UI, and the details that shape how a Burro feels to work alongside, down to what the lights do. The team is five (5) engineers today, with room to grow as the product scales.\nThis team also builds the platform the rest of engineering builds on. Autonomy, Perception, and SLAM ship capabilities; this team turns them into behavior a customer can see and use. That increasingly includes AI running on the robot itself. We are bringing voice models to the edge so a worker in a nursery can talk to a Burro and have it respond without a network connection, and this team owns it end to end: on-device inference, the language understanding that maps a spoken request to a mission, and what the robot does when the model gets it wrong.\nThis is a hands-on director role. You will run the team, and you will also be in the code. This role is designed for a leader who remains deeply committed to technical execution and engineering excellence.\nThe ideal candidate has built and shipped scalable software on real robots or autonomous vehicles, and has managed engineers before. You will sit alongside our directors of Platform and Integration, SLAM, and Perception, and partner closely with Hardware, Product, and Field Operations.\n","salary_min":160000,"salary_max":180000,"location":"Philadelphia, PA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["nlp","autonomous-vehicles","robotics","computer-vision"],"apply_url":"https://jobs.lever.co/Burro/355e0808-b5e1-4cc4-93ac-ca6287c5dcf7/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-17T19:42:23.279Z","expires_at":"2026-09-29T13:46:53.600374Z","created_at":"2026-08-25T18:32:42.947588Z","updated_at":"2026-08-30T13:46:53.735141Z","company_name":"Burro","company_slug":"burro","company_logo_url":"https://www.google.com/s2/favicons?domain=burro.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/870c8dc8-5777-448d-8df3-6185edbad22d"},{"id":"09cc77a9-0b4b-49a6-ada6-446f95619ce6","company_id":"a0000000-0000-0000-0000-000000000009","title":"Member of Technical Staff, Multilingual","slug":"member-of-technical-staff-multilingual-c99001f8","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\nRole Overview:\n\nWe are looking for world-class research scientists and research engineers to build cutting-edge multilingual AI to serve the world!\n\nAt Cohere, we care deeply about building technologies that are broadly accessible and useful, regardless of language.  As a Member of Technical Staff on the Multilingual team, you'll be at the forefront of advancing language models that serve the world. You’ll push the boundaries of what's possible in natural language processing. This isn't just a technical role—it's an opportunity to contribute to groundbreaking research that will define the next generation of AI.\n\n\n\n\nKey Responsibilities:\n\n - Lead the design and implementation of scalable solutions to improve multilingual LLM performance across a wide variety of skills – if we need it to make a great multilingual model, you can build it!\n\n - Is perfect for someone passionate about languages and AI, with a keen eye for detail and strong technical skills.\n\n - Offers the opportunity to contribute to cutting-edge language technology, making a global impact.\n\n - Requires a self-starter who can work independently and deliver results efficiently.\n\n - Publish research findings and contribute to academic discourse in top-tier venues\n\n - Mentor junior team members and shape global best practices in multilingual AI / NLP\n   \n   \n\nQualifications:\n\n - PhD in Computer Science, Linguistics, or related field (or equivalent experience)\n\n - Proven track record in large-scale data processing and ML pipeline development\n\n - Expert in Python and software engineering best practice\n\n - Deep understanding of multilingual data challenges and NLP fundamentals\n\n - Passion for advancing language technology and making global impact\n\n - Strong publication record or demonstrated research potential\n\n - Excellent communicator able to bridge technical and research communities\n   \n   \n\nNote:\n\n - This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.\n\n - If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply.\n\n\nWe value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations request form and we will work together to meet your needs.\n\n\n\n\nCompensation:\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 - For candidates in the US, the Compensation Range is: $110,000 - $370,000 [USD]\n\n - For candidates in Canada, the Compensation Range is: $165,000 - $460,000 [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 enrichment benefits:\n   \n   Arts \u0026 culture, fitness/wellness, quality time, and a workspace improvement credit.\n   \n   Education \u0026 learning stipend for conferences, courses, and coaching.\n\n - 6 weeks of paid vacation (30 working days!)\n\n - Budget for traveling to other offices if you are remote, plus an annual company offsite.\n\n\n\n\nHOW AND WHERE WE WORK:\n\n - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.\n\n - For those in the office: a daily lunch program, plenty of snacks, and re","salary_min":165000,"salary_max":460000,"location":"London, UK","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["payments","llm","nlp","search"],"apply_url":"https://jobs.ashbyhq.com/cohere/a87be947-00f0-4a4c-a690-a4922f88f553/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-17T15:57:25.097Z","expires_at":"2026-09-29T13:31:52.3333Z","created_at":"2026-06-28T14:01:33.291718Z","updated_at":"2026-08-30T13:31:52.473166Z","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/09cc77a9-0b4b-49a6-ada6-446f95619ce6"},{"id":"8833a326-2222-405d-9178-38d091a4acf2","company_id":"40ad6923-4b5c-44e5-b30c-340bb35deab6","title":"Senior Machine Learning Engineer ","slug":"senior-machine-learning-engineer-5107596c","description":"About Us:\n\nHere at Ambience, we never set out to be just another scribe. We’re building the AI intelligence platform that restores humanity to healthcare and drives meaningful ROI for health systems across the country.\n\nOur technology helps providers focus on delivering great care by removing the administrative burden that pulls them away from patients and away from their most impactful work. Ambience delivers real-time coding-aware documentation and clinical workflow support across ambulatory, emergency and inpatient settings at the top health systems in North America.\n\nOur teams operate relentlessly with extreme ownership to build the best solutions for our health system partners. We value candor, positivity and deep thought — and we expect a lot from each other because we know the problems we’re solving truly matter.\n\nAmbience was ranked #1 for Improving the Clinician Experience in the KLAS Research Emerging Solutions Top 20 Report, recognized by Fast Company as one of the Next Big Things in Tech, named one of the best AI companies in healthcare by Inc., and selected as a LinkedIn Top Startup in 2024 and 2025. We’re backed by Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, and Kleiner Perkins — and we’re just getting started.\n\n\n\n\nTHE ROLE:\n\nAs a Senior Machine Learning Engineer at Ambience, you will build and improve the AI systems that power our clinical products. You’ll own complex projects end-to-end, from diagnosing production failures and designing evaluations to building, deploying, and iterating on model and agentic systems.\nThis is a highly hands-on role with significant technical ownership. You’ll work closely with clinicians, product managers, and fellow engineers to translate cutting-edge research into reliable, production-grade AI systems.\n\nOur engineering roles are hybrid — working onsite at our San Francisco office three days per week.\n\n\n\n\nWHAT YOU’LL DO:\n\n - Build Trustworthy AI Evaluation Systems: Design and own evaluation pipelines for LLM and agentic systems, combining automated graders, regression testing, production feedback, and human evaluation to measure real product quality.\n\n - Improve Production Model Behavior: Diagnose high-impact failure modes and test improvements across prompting, retrieval, context, routing, data, fine-tuning, or other model and system interventions.\n\n - Build Agentic AI Systems: Develop production systems involving tool use, retrieval, context and state management, routing, orchestration, tracing, and failure recovery.\n\n - Build Data and Improvement Flywheels: Turn production failures and user feedback into better datasets, evaluations, and model behavior through active learning and systematic iteration.\n\n - Stay at the Cutting Edge: Distill insights from recent research in LLMs, agents, NLP, speech, and multimodal AI and translate promising ideas into practical experiments.\n\n - Own AI Systems End-to-End: Work across models, data, evaluation, orchestration, serving, and observability, while remaining deeply hands-on in code and production debugging.\n\n\n\n\nWHO YOU ARE: \n\n -  Strong Production AI Experience\n   5+ years in production ML, research engineering, or applied AI.\n   Have built a consequential production AI system or materially improved model behavior in production.\n   Strong understanding of modern LLMs, transformers, and production AI systems.\n\n - Deep Evaluation Experience\n   Experienced designing evaluations for LLMs, agents, or other complex AI systems.\n   Can turn ambiguous quality problems into measurable dimensions, datasets, and experiments.\n   Familiar with challenges such as grader bias, leakage, misleading aggregate metrics, regression detection, and offline-online mismatch.\n\n - Agentic Systems Experience\n   Experience building production systems involving multiple models, tools, retrieval, context, state, routing, or orchestration.\n   Understands reliability and failure modes in complex AI workflows, not just individual model calls.\n\n - Production-Grade Software Engineer\n   Proficient in Python and modern ML frameworks; PyTorch preferred.\n   Comfortable with deployment, observability, CI/CD, and containerized systems.\n   Still highly hands-on: writes code, inspects traces, analyzes failures, and debugs production systems.\n\n - Data-Centric AI Developer\n   Skilled at building high-quality datasets and feedback loops.\n   Experienced using production failures, user feedback, and active learning to improve model and system quality.\n\n - Effective Interdisciplinary Collaborator\n   Able to work closely with clinicians, product managers, and fellow engineers.\n   Strong communicator who can simplify complex AI concepts for diverse audiences.\n   Comfortable owning ambiguous technical problems and driving them to measurable outcomes.\n   \n   \n   Nice-to-Haves\n\n - Experience with realtime voice, conversational AI, or multimodal systems.\n\n - Experience with fine-tuning, post-training, or model adaptation.\n\n - Prior work i","salary_min":225000,"salary_max":300000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","generative-ai","payments","llm","agents","search","healthcare","nlp"],"apply_url":"https://jobs.ashbyhq.com/ambiencehealthcare/6f44370e-1979-4237-a3db-94c46ec7ec9c/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-11T16:31:17.016Z","expires_at":"2026-09-29T13:37:47.545943Z","created_at":"2026-08-25T18:28:24.330364Z","updated_at":"2026-08-30T13:37:47.678173Z","company_name":"Ambience Healthcare","company_slug":"ambience-healthcare","company_logo_url":"https://www.google.com/s2/favicons?domain=ambience.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8833a326-2222-405d-9178-38d091a4acf2"},{"id":"741866cf-ead6-4e1c-9ab9-de92c040f40f","company_id":"4bc4e268-7a05-4a65-a162-1688af546f7e","title":"Machine Learning Intern","slug":"machine-learning-intern-5bbef37c","description":"WHAT MAKES US EPIC?\n At the core of Epic’s success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it’s building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we’re always innovating.\n Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development.\n ENGINEERING - SPECIAL PROJECTS\n What We Do \n The Special Projects team at Epic is responsible for executing high-impact projects that push the envelope to define the future of real-time graphics and gaming technology (The Matrix Awakens, Lumen in the Land of Nanite). In collaboration with the Unreal Engine team, we strive to put our technology and knowledge into the hands of users, empowering developers and content creators with the most powerful suite of real-time tools in the world.\n MACHINE LEARNING RESEARCH INTERNSHIP AT EPIC GAMES\n What You'll Do \n Epic Games is looking for current PhD students and recent PhD or MSc graduates (within 12 months of graduation) for paid, 6-12 month research internships with our Special Projects \u0026 Epic Research Group. You will work with our team of research scientists and engineers at the intersection of vision, language, speech processing and game development to create machine learning models in a range of areas to support game developers and improve user experience.\n In this role, you will \n \n Create machine learning models in areas including player safety, game agents (e.g. AI-backed characters, VLA agents), world/scene and game logic generation, developer tools, and improved user experience\n Work alongside our team of research scientists and engineers on applied research problems\n Own data analysis and data creation, supported by an internal team of labellers\n Design, implement, and experiment with models end to end\n Gain exposure to engineering work around deploying models at scale\n \n What we're looking for \n \n An ongoing or recently completed (within the last 12 months) PhD in Computer Science, Mathematics, AI or a related field - recent MSc graduates in the same fields will also be considered\n Experience building models or algorithms in computer vision, natural language processing, or speech/audio/acoustic processing\n Hands-on knowledge of modern deep learning methods, such as Transformers, LLM fine-tuning, and diffusion models\n Strong coding skills in Python and the standard ML stack (PyTorch, NumPy, SciPy, scikit-learn)\n Desirable: Game dev experience in either C++ or C# (including personal projects)\n \n Internship Details \n \n Duration: 6-12 months, with flexible start dates throughout 2026/2027\n Hours: full-time (40 hours/week) or part-time (20 hours/week)\n Location: Select regions within the UK, US or Canada\n Employment Authorization: You must hold an existing right to work in the UK, US or Canada for the full duration of the internship - Visa sponsorship or support is unavailable for this role\n \n This role is open to multiple locations across North America and Europe (including CA, NYC, \u0026 WA). \n This internship has a flexible start date in 2026/2027. Recruitment will be ongoing until teams find an ideal match. Applicants must be legally authorized to work in the posting location for the duration of the internship. For more information about Epic’s Early Career Program, visit epicgames.com/earlycareers . This is going to be Epic! \n Pay Transparency Information \n The expected annual base pay range(s) for this position are detailed below. Each base pay range is relevant only for individuals who are residents of or will be expected to work within the specified locale. Compensation varies based on a variety of factors, which include (but aren’t limited to) things such as skills and competencies, qualifications, knowledge, and experience. In addition to base pay, most employees are eligible to participate in Epic’s generous benefit plans and discretionary incentive programs (subject to the terms of those plans or programs). \n New York City Base Pay Range\n $139,029 — $166,834 USD \n California Base Pay Range\n $122,345 — $146,814 USD \n Washington Base Pay Range\n $111,223 — $133,468 USD \n ABOUT US\n Epic Games​ ​is a leading interactive entertainment company. For over 30 years we've been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarka","salary_min":111223,"salary_max":133468,"location":"BLANK,BLANK,Multiple Locations","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["diffusion-models","deep-learning","fine-tuning","pytorch","nlp","llm","computer-vision","machine-learning"],"apply_url":"https://epicgames.com/careers/jobs/6138134004?gh_jid=6138134004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-07T16:12:54Z","expires_at":"2026-09-29T13:47:27.420832Z","created_at":"2026-08-25T18:32:57.991607Z","updated_at":"2026-08-30T13:47:27.55394Z","company_name":"Epic Games","company_slug":"epic-games","company_logo_url":"https://www.google.com/s2/favicons?domain=epicgames.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/741866cf-ead6-4e1c-9ab9-de92c040f40f"},{"id":"f9964c61-3296-4c8b-a011-840274e46025","company_id":"e12d7a84-7538-4599-9b03-0cce91dc76b4","title":"Staff Backend Engineer, Architecture Engineering: Nonlinear Productivity","slug":"staff-backend-engineer-architecture-engineering-nonlinear-productivity-b2053195","description":"GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.\n The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.\n * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. \n An overview of this role \n As a Staff Engineer, you'll be the technical anchor for GitLab's Nonlinear Productivity team in the US: the person who decides what \"proven\" means before something ships, and who helps shape what the team builds next, not just how to build it. It's a from-scratch, generalist team with no dedicated product manager — that ownership starts on day one.\n Some examples of the problems this team takes on:\n \n Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions.\n Turning a manual, error-prone release step into an agentic workflow that catches its own mistakes before a human ever has to.\n \n What you'll do \n \n Set the technical direction for the team's agentic systems, from how agents are orchestrated to where a step should stay human-owned, and defend those calls once they're tested against real code.\n Discover and prioritize sources of friction across GitLab's SDLC, driving the fix — agentic, process-based, or both — from a rough hypothesis through to a shipped, measured result.\n Work across any part of GitLab's codebase as the problem requires, since this team operates like a small, generalist group rather than one scoped to a single service.\n Apply distributed systems judgment to catch cases where generated code looks correct but breaks under concurrency, at scale, or across deployment topologies (including self-managed, dedicated, and multi-tenant environments), and coach others to do the same.\n Mentor senior and mid-level engineers on agent engineering practices and distributed systems judgment, through design reviews and pairing that raise the team's collective bar rather than just your own output.\n Collaborate with the India-based group a few times a week to align on the roadmap, and represent the team's technical progress to stakeholders in the Chief Technology Officer's organization.\n Serve as a bar raiser for the team's hiring, owning the Technical Leadership round for other Staff-level candidates as the team scales.\n Own a greenfield technical foundation from day one, with your scope and impact free to grow as the team scales.\n \n What you'll bring \n \n Experience building reliable agentic or large language model (LLM)-based systems, including multi-step orchestration, tool use, guardrails, and recovery.\n Ability to work autonomously in unfamiliar codebases and drive solutions from discovery through completion.\n Strong distributed systems and computer science fundamentals, including coordination, consistency, idempotency, rate limiting, failure modes, and degradation under load.\n Proficiency in Go, Rust, or Python, with the ability to read and modify code in the others.\n A track record of delivering results from unclear or incomplete requirements — able to take a complex, loosely specified problem and decompose it into a concrete proposal of small, shippable steps.\n Experience designing evaluation frameworks for systems where \"looks plausible\" and \"is actually correct\" are different questions, and a track record of raising the quality bar for a team's output, not just your own.\n A history of unblocking and enabling teammates — through design reviews, technical writing, or mentoring — and of engaging regularly with other teams to find where collaboration actually pays off.\n \n About the team \n Nonlinear Productivity — shortened internally to \"NLP,\" with no relation to natural language processing — is one of GitLab's newest teams: a strategic incubation group that reports into AI Platform leadership under the direct sponsorship of the CTO. It's s","salary_min":152800,"salary_max":259200,"location":"Remote (Canada)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["nlp","llm","distributed-systems","agents","backend"],"apply_url":"https://job-boards.greenhouse.io/gitlab/jobs/8646544002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-06T00:44:04Z","expires_at":"2026-09-29T13:39:07.670601Z","created_at":"2026-08-25T18:28:59.021218Z","updated_at":"2026-08-30T13:39:07.802955Z","company_name":"GitLab","company_slug":"gitlab","company_logo_url":"https://www.google.com/s2/favicons?domain=about.gitlab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f9964c61-3296-4c8b-a011-840274e46025"},{"id":"5b08041d-6d99-4003-a485-6b9120370de6","company_id":"e12d7a84-7538-4599-9b03-0cce91dc76b4","title":"Senior Backend Engineer, Architecture Engineering: Nonlinear Productivity","slug":"senior-backend-engineer-architecture-engineering-nonlinear-productivity-bcfba4f9","description":"GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.\n The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.\n * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. \n An overview of this role \n As a Senior Backend Engineer on GitLab's Nonlinear Productivity team, you'll find and remove friction across the software development lifecycle using reliable AI-powered automation — diagnosing problems like long review cycles, manual release steps, and brittle automation, then building the automation and process changes that resolve them for good.\n Some examples of the problems this team takes on:\n \n Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions.\n Turning a manual, error-prone release step into an agentic workflow that catches its own mistakes before a human ever has to.\n \n What you'll do \n \n Identify sources of friction across GitLab's software development lifecycle and scope agentic solutions to address them, turning vague pain points into concrete, buildable proposals.\n Design and build reliable AI-powered systems that follow step-by-step workflows, use tools and safety checks, and correct errors before taking engineering action — the kind of output you can actually trust with real engineering decisions.\n Build and maintain evaluation tools that judge agent output on correctness, constraint compliance, and cost, not on whether it merely \"seems to work.\"\n Work across GitLab's codebase as each problem requires, going wherever the friction actually is rather than staying inside one service or product area.\n Apply distributed systems judgment to identify generated code that may fail under concurrency, at scale, or across self-managed, dedicated, and multi-tenant deployments, catching failures before they reach customers.\n Collaborate with the India-based group, sharing roadmaps, findings, and reusable agent tooling\n Take ownership of a greenfield problem space from day one, helping shape a proven internal fix into a capability GitLab could offer customers externally, with your scope and impact free to grow as the team scales.\n \n What you'll bring \n \n Hands-on experience building agentic or large language model-based systems — multi-step orchestration, tool use, guardrails, and recovery patterns — and making them reliable in production, not treated as one-off prompts or demonstrations.\n A track record of working autonomously in unfamiliar codebases, getting oriented quickly, and driving solutions through completion.\n Strong distributed systems knowledge, including coordination, consistency, idempotency, rate limiting, failure modes, and degradation under load.\n Proficiency in Go, Rust, or Python, in that order of team priority, and the ability to read and modify code in the other languages.\n Helpful experience includes shipping autonomous agents that complete real tasks from start to finish; improving build systems, release processes, review workflows, or other parts of the software development lifecycle; and working with globally distributed teams, large language model workload costs, or production constraints across on-premises, air-gapped, single-tenant, and software-as-a-service deployments.\n \n About the team \n Nonlinear Productivity — shortened internally to \"NLP,\" with no relation to natural language processing — is one of GitLab's newest teams: a strategic incubation group that reports into AI Platform leadership under the direct sponsorship of the CTO. It's split into a US group (this role) and an India-based group working the same charter; the two sync on roadmap and tooling a few times a week but otherwise run day to day on their own. It operates like a startup — no dedicated product manager, no pre-set backlog — and solutions ","salary_min":139200,"salary_max":235200,"location":"Remote (Canada)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["llm","agents","nlp","distributed-systems","backend"],"apply_url":"https://job-boards.greenhouse.io/gitlab/jobs/8646556002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-06T00:22:22Z","expires_at":"2026-09-29T13:39:06.799763Z","created_at":"2026-08-25T18:28:58.991001Z","updated_at":"2026-08-30T13:39:06.941834Z","company_name":"GitLab","company_slug":"gitlab","company_logo_url":"https://www.google.com/s2/favicons?domain=about.gitlab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5b08041d-6d99-4003-a485-6b9120370de6"},{"id":"75ab7ab1-c36f-46c6-80cb-96350b135062","company_id":"37683849-8d19-405f-a4f6-9015ab2a4fed","title":"Head of Product Marketing (Toronto, Canada)","slug":"head-of-product-marketing-71a36bdb","description":"PolyAI is the Agentic Dialog Platform for building the conversational enterprise, used to build, run, govern, and improve dialog agents at scale. Powered by Raven, a proprietary dialog model trained on more than a billion enterprise conversations, PolyAI agents are built for complexity, open at every layer, and sovereign by design. PolyAI serves hundreds of enterprises across 75 languages and 25 countries, including Metro Bank, Marriott, PG\u0026E, and UniCredit. \n The Head of Product Marketing, Voice Assistants will join PolyAI’s rapidly growing marketing team. This role will own PolyAI’s core product messaging, positioning, and competitive intelligence functions. In the first few months, the person filling this position will take stock of PolyAI’s product messaging, go-to-market motions, and our key competitors. Once fully onboarded, the Head of Product Marketing, Voice Assistants will own all product messaging and be responsible for ensuring all PolyAI team members can clearly articulate our products' unique value. \n Responsibilities:  \n \n Create a product marketing strategy that enables the marketing team to consistently deliver on-brand and on-message experiences through analyst relations, content, demand generation  \n Influence our win rate through improved go-to-market strategy and enablement \n Develop resonant messaging and positioning that drives commercial outcomes for PolyAI’s world-leading voice AI products \n Catalog an understanding of PolyAI’s direct and indirect competitors and ensure that our messaging is differentiated \n Work with marketing and sales leadership to prioritize market segments and develop personas that support the content and demand generation functions \n Work with content and sales enablement team members to develop collateral that reduces friction in the sales process and increases revenue \n Build our customer understanding and market insight through customer interviews, partnerships, and industry experts  \n Support enablement initiatives across the entire revenue organization \n Create and maintain an organized and accessible database of competitive intelligence for sales, marketing, and executive leadership \n Collaborate with content team leads on thought leadership strategy and regularly contribute to the function \n Scale and lead the product marketing organization as Poly grows \n Be a capable spokesperson for the organization, both online and in-person \n \n Minimum skills and experience: \n \n 8+ years of experience in B2B tech marketing \n 3+ years of experience in a product marketing role  \n \n Preferred skills and experience: \n \n Knowledge of CCaaS, UCaaS, or Call Center technology markets \n Knowledge of NLP, NLU, or other machine-learning technology \n \n We provide a competitive salary range for this role - which is  $320,000-$420,000 OTE - depending on level and experience. Please note this range is intended as a guide, not a guarantee. Final compensation will be based on individual qualifications, relevant experience, and the scope of the role. \n \n Benefits \n 💰 Participation in the company’s employee share options plan \n 🏝 Flexible PTO policy \n 📚 Annual learning and development allowance: We will reimburse the costs of any certified and non-certified training, including conferences, events, books and subscriptions that are relevant to your role at PolyAI, in addition to any formal training that the company offers \n 🏡 We’re all about making WFH work for you - that’s why we offer a one-off WFH allowance when you join. Offering perks like noise-cancelling headphones or a comfortable desk chair to boost your comfort and focus! \n 🏥 Healthcare plan: We offer health insurance through Allianz. Full details on the plan will be shared with you on your first day \n 🌎  Sabbatical Program: 5-week paid sabbatical available after 5 years of employment \n \n At PolyAI, we take great pride in our values - they guide everything we do. We believe that a strong culture leads to meaningful work and lasting impact. \n Our core values are: \n Only the best We expect the best from our people, we hire people that expect the best from themselves, and we nurture this drive for excellence. \n Ownership We care deeply about what we do. We take ownership of our initiatives, decisions and outcomes. \n Relentlessly improve We demand more from ourselves and are always evolving. Continuous, obsessive improvement is the only way we will transform the world of conversational AI. \n Bias for action Our world moves quickly and so do we. We take calculated risks and we deliver impact fast. \n Disagree and commit We are all working toward the same goal. If we donʼt agree with something, we work hard to understand it and when a decision is made, we accept it and give it our all. \n Build for people We want the world to enjoy the experiences they have with us. We are building for a future that prefers automation. \n \n PolyAI is proud to be an equal-opportunity employer. We celebrate diver","salary_min":320000,"salary_max":420000,"location":"Canada, United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","speech","nlp","healthcare"],"apply_url":"https://job-boards.eu.greenhouse.io/polyai/jobs/4945695101","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T16:26:05Z","expires_at":"2026-09-29T13:38:28.341285Z","created_at":"2026-08-25T18:28:42.464898Z","updated_at":"2026-08-30T13:38:28.480523Z","company_name":"PolyAI","company_slug":"polyai","company_logo_url":"https://www.google.com/s2/favicons?domain=poly.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/75ab7ab1-c36f-46c6-80cb-96350b135062"},{"id":"87f4465c-c163-4dc4-a372-c7dac502d39a","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Sr. Manager, Machine Learning Engineering-Applied Research","slug":"sr-manager-machine-learning-engineering-applied-research-3ec4b562","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 Pinterest is on a mission to bring everyone the inspiration to create a life they love. The Applied Science team plays a critical role in this mission by developing cutting-edge machine learning solutions that scale across all of Pinterest engineering teams (see our team’s  publications ).\n  \n We're looking for a highly technical Engineering Manager with a deep understanding of modern recommendation systems to manage, lead and develop a team of machine learning researchers and engineers within the Applied Science team.  In this role, you will help the team build a portfolio of work which can balance that addresses both immediate short-term business needs and long-term strategic breakthroughs.  You will partner with senior leaders to evolve our technical roadmap and directly drive Pinterest’s core mission forward. \n  \n What you will do: \n \n Vision and Strategy: Own the technical roadmap and strategic vision for Pinterest’s next-generation recommendation systems. Champion the use of state-of-the-art ML techniques to deliver revolutionary innovations in recommendation technology.\n Research to Production: Successfully transition breakthrough ML research into production-ready systems that directly impact core company metrics.\n Team Leadership and Culture: Manage, inspire, and develop a talented team of machine learning researchers and engineers specializing in recommendation systems. Partner with your team to define their charter, ensuring a strong balance between cutting-edge research and building foundational embeddings that benefit products across the entire company.\n Cross-functional Collaboration: Collaborate with Core Engineering, Ads Engineering, Infrastructure, Content, and Data Science teams to prototype, build, and scale solutions to complex engineering challenges. Partner with leadership to deepen user understanding and set the strategic direction for our recommendation system roadmap.\n \n  \n What we are looking for: \n \n Technical Depth: 7+ years of combined post-graduate academic and industry experience applying state-of-the-art ML technologies to real-world problems on web-scale data, alongside 3+ years of direct people management experience.\n Proven Execution: A track record of delivering high-impact initiatives across multiple product areas, with a demonstrated ability to influence peers and leadership using data-driven insights.\n Talent Development: Experience mentoring, coaching, and up-leveling software and machine learning engineers.\n Continuous Learner: A self-propelled learner who stays ahead of industry trends, new tools, and emerging methodologies, with an appetite for building proof-of-concept prototypes.\n Business \u0026 Product Acumen: The ability to transform vague, ambiguous questions into well-defined projects with clear success metrics that drive business decisions.\n Communication \u0026 Credibility: Excellent communication skills with the ability to distill complex technical findings for leadership and product teams, backed by a strong track record of publications in machine learning, AI, data science, or related technical fields.\n Academic Credentials: MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field\n Nice to have: \n \n Track record of publishing at top-tier ML/RecSys conferences (KDD, RecSys, NeurIPS, CVPR).\n Experience leveraging modern LLM/Agentic workflows and generative AI capabilities to accelerate engineering productivity and context extraction.\n \n \n  \n In-Office Requirement Statement: \n \n We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.\n This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in th","salary_min":227871,"salary_max":469147,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["llm","nlp","agents","generative-ai","machine-learning","research"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8015504","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-04T20:37:06Z","expires_at":"2026-09-29T13:38:54.704077Z","created_at":"2026-08-25T18:28:55.571383Z","updated_at":"2026-08-30T13:38:54.841436Z","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/87f4465c-c163-4dc4-a372-c7dac502d39a"},{"id":"3369fa89-a50f-4c90-b873-23a405ec98aa","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Staff Scientist, Bioinformatics/RWD","slug":"staff-scientist-bioinformaticsrwd-722aee14","description":"Natera is seeking an innovative and driven bioinformatics scientist to lead and conduct cutting-edge real-world evidence (RWE) analyses and predictive analytics across oncology, organ health, and women’s health datasets. This unique role blends expertise in bioinformatics, artificial intelligence (AI), machine learning (ML), and the manipulation of complex real-world data (RWD). Candidate will leverage advanced AI methodologies to extract actionable clinical insights from vast multimodal datasets (genomics, clinical, demographic), driving impactful data visualization and advancing our application of genomics in a real-world clinical setting. The ideal candidate should have strong project management skills, and a keen eye for visualizing complex data in an impactful way to advance our understanding and application of genomics in a real-world setting. \n Key Responsibilities: \n \n Bioinformatics  \u0026 Genomic Analysis : Lead the analysis of large-scale cancer and germline multi-omics datasets to extract meaningful insights. Utilize and augment traditional bioinformatics tools with AI-driven techniques to interpret genomic data within the context of RWE studies \n RWD/RWE Analysis : Lead the extraction, curation, and analysis of large-scale RWD sources, including Electronic Health Records (EHR), claims data, and patient registries. Design and execute robust RWE studies to support clinical, commercial, and regulatory objectives. \n Data Integration and Management : Facilitate the integration of omics data with other types of data (clinical, demographic, etc.) to enrich the analyses. Manage large datasets and ensure data integrity and confidentiality. \n AI \u0026 Predictive Analytics : Develop, train, and deploy advanced artificial intelligence and machine learning models (e.g., Deep Learning, NLP, ensemble methods) to forecast trends, patient outcomes, and biomarker discovery using RWD and genomics data. Apply state-of-the-art AI frameworks to identify hidden patterns that inform clinical decision-making and product strategy. \n Unstructured Data Integration : Facilitate the integration of highly complex, multimodal datasets. Utilize NLP and LLMs to extract valuable structured insights from unstructured clinical notes, pathology reports, and other disparate RWD sources. Manage large datasets while ensuring strict data integrity and confidentiality. \n Project Management : Oversee and manage RWD and genomics projects from inception to completion. Ensure that projects are completed on time, within budget, and meet high-quality standards. \n Cross-Functional Collaboration : Work closely with other departments such as R\u0026D, Data Science, Business Development, Medical Affairs, Product Management, and Engineering to integrate genomics and clinical data into broader research and development initiatives. \n Reporting and Communication : Present complex RWE data and analyses in a clear and comprehensible manner to a variety of audiences, including non-experts. Prepare detailed reports and publications. \n Innovation and Development : Stay abreast of the latest developments in genomics and bioinformatics. Propose and develop new methods and technologies for advanced data analysis. \n Stakeholder Engagement : Engage with key stakeholders to define project goals, report progress, and discuss findings. Act as a liaison between the technical team and non-technical stakeholders. \n \n Desired qualifications: \n \n Ph.D. in Bioinformatics, Computational Biology, Genetics, or a related field \n At least 10 years of relevant experience  \n Proven expertise in bioinformatics, particularly in genomics data analysis. Demonstrated expertise in cancer genomics, including genomic alterations, molecular pathways, and cancer biology \n Expert knowledge of bioinformatics tools including mapping, variant calling, CNV analysis and statistical methods \n Strong experience in managing, querying, and analyzing massive-scale genomic and healthcare datasets using SQL, Python, or R, and data visualization tools \n Additional expertise in germline genetics, particularly in relation to organ health and prenatal health, is a significant plus. \n AI/ML Expertise: Proficiency in predictive analytics, advanced machine learning, deep learning, and statistical modeling. Strong hands-on experience with AI frameworks such as PyTorch, TensorFlow, Keras, etc. \n Understanding of real-world clinical data, such as electronic health records, claims data, patient registries, health surveys. Familiarity with common data models (e.g., OMOP) and experience utilizing NLP/LLM to parse unstructured clinical data.  \n Ability to interpret clinical endpoints, understand patient cohorts, and collaborate with clinical stakeholders \n Knowledge of translational medicine and/or early discovery in the biotech or pharmaceutical industry is a plus \n Excellent project management skills with a proven track record in leading successful projects \n Experience managing one or more direct/indirect reports. \n ","salary_min":158000,"salary_max":197500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["pytorch","healthcare","tensorflow","llm","nlp","deep-learning"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6128396004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-03T23:26:50Z","expires_at":"2026-09-29T13:40:55.373148Z","created_at":"2026-08-25T18:29:44.043734Z","updated_at":"2026-08-30T13:40:55.504432Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3369fa89-a50f-4c90-b873-23a405ec98aa"},{"id":"7c5fdde0-ad3f-434d-939b-9cf8a5c44b80","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Machine Learning Engineer, Assistant Quality","slug":"machine-learning-engineer-assistant-quality-86fe2f88","description":"About Glean: \n  \n Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. \n  \n At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. \n  \n Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. \n  \n If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. \n \n  \n About the Role: \n  \n Glean is seeking a Machine Learning Engineer to improve the quality of our AI Assistant and autonomous agents. This role sits at the intersection of production machine learning, LLM-powered systems, and product engineering, with a focus on building, evaluating, and iterating on assistant experiences that are useful, reliable, and grounded in real enterprise workflows. \n You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration. The ideal person is excited by shipping production systems, not pure research, and wants to help shape how Glean’s assistant gets better over time through stronger signals, tighter feedback loops, and better end-to-end execution quality. \n  \n You will:  \n \n \n Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows. \n Design evaluation, benchmarking, and monitoring loops to measure assistant quality, model quality, and end-to-end system performance. \n Develop and iterate on signals, prompts, workflows, and model-driven logic that improve reasoning, planning, personalization, and task completion quality. \n Work across areas such as RAG, semantic search, recommendation-style systems, post-training or reinforcement learning, and agent orchestration where they materially improve product outcomes. \n Partner closely with product, design, and engineering teammates to understand customer pain points and ship high-quality production systems quickly. \n Contribute to the data and ML infrastructure needed to support robust experimentation, offline and online evaluation, and continuous model improvement. \n \n About you: \n \n \n 2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership. \n Strong hands-on coding ability and a track record of shipping production systems, not just prototypes or research projects. \n Experience in one or more of the following areas: LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization. \n Comfort working across both modeling and product engineering details, including experimentation, quality measurement, and production iteration. \n Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++. \n A pragmatic, product-minded approach. You know when to use sophisticated ML techniques and when simple, reliable systems are the better answer. \n A proactive, low-ego working style and excitement about learning quickly in a high-velocity environment. \n \n Location: \n \n \n This role is hybrid (4 days a week in our San Francisco office) \n \n Compensation \u0026 Benefits: \n  \n The standard base salary range for this position is $180,000 - $205,000 annually. ","salary_min":180000,"salary_max":205000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["nlp","llm","agents","search","reinforcement-learning","cloud","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4711484005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-03T21:43:08Z","expires_at":"2026-09-29T13:34:06.343999Z","created_at":"2026-08-25T18:27:05.972445Z","updated_at":"2026-08-30T13:34:06.480743Z","company_name":"Glean","company_slug":"glean","company_logo_url":"https://www.google.com/s2/favicons?domain=glean.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7c5fdde0-ad3f-434d-939b-9cf8a5c44b80"},{"id":"426da38a-255b-4b18-aa49-edd706e59a31","company_id":"6ea0f41a-b13e-481a-b410-5195f391f939","title":"Research Engineer, Large-Scale Training","slug":"research-engineer-large-scale-training-19a25c49","description":"About the Role \n The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. \n As a Research Engineer on the Scaling Team within Model Shaping, you will turn cutting-edge research on efficient foundation model training into robust, high-performance systems. You will profile and optimize Together's training infrastructure, identify performance bottlenecks across the stack, and implement state-of-the-art techniques from both the research literature and our own scientists in production environments. \n Your work will directly shape the fine-tuning experience of Together's customers. You will rapidly bring newly released open-source models onto the Model Shaping platform, ensuring they train efficiently and reliably across diverse customer workloads. Working closely with Research Scientists, you will also build the experimental infrastructure that accelerates research and enables validated ideas to be deployed reliably at scale. \n Responsibilities \n \n Design, implement, and optimize core components of Together's large-scale training infrastructure. \n Integrate new model architectures, validate training correctness and convergence, and optimize performance for production fine-tuning workloads. \n Profile distributed training workloads to identify and eliminate bottlenecks across compute, memory, and communication. \n Design and execute experiments to validate performance hypotheses and benchmark new approaches against state-of-the-art methods. \n Partner closely with Research Scientists to productionize novel training methods and contribute to publications and open-source releases. \n Rapidly enable support for newly released open-source foundation models on the Together platform. \n Build and maintain experimental infrastructure that accelerates research while ensuring production-quality reliability and scalability. \n \n Requirements \n \n Demonstrated ability to independently take ambiguous performance or infrastructure problems from investigation through deployment. \n Strong programming skills in Python and PyTorch, with an emphasis on writing efficient, maintainable code. \n Hands-on experience training or fine-tuning large neural networks in multi-GPU or multi-node environments. \n Solid understanding of ML systems fundamentals, including GPU architecture, mixed-precision training, and distributed training paradigms such as data, tensor, pipeline, or expert parallelism. \n Strong communication skills and the ability to collaborate effectively with both researchers and engineers. \n Passion for staying current with advances in AI research and applying them to real-world systems. \n Excitement about translating cutting-edge research into production systems that deliver customer impact. \n \n Nice to Have \n \n Experience writing optimized NVIDIA GPU kernels using CUDA or Triton, or implementing communication collectives with technologies such as NCCL or NVSHMEM. \n Experience with large-scale training frameworks such as FSDP, DeepSpeed, Megatron-LM, or custom distributed training systems. \n Experience optimizing distributed training for compute efficiency, memory efficiency, or scalability. \n Experience running and managing large-scale GPU experiments, including scheduling, monitoring, and fault tolerance. \n Contributions to widely used open-source ML or ML systems projects. \n Experience building or operating ML products or managed services used by external customers. \n \n About Together AI \n Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, ATLAS, RedPajama, and Mamba. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. \n Compensation \n We offer competitive compensation, startup equity, health insurance, and other benefits. The US base salary range for this full-time position is $200,000 - $290,000. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. \n Equal Opportunity \n Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone reg","salary_min":200000,"salary_max":290000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","search","fine-tuning","gpu","nlp","generative-ai","pytorch","deep-learning"],"apply_url":"https://job-boards.greenhouse.io/togetherai/jobs/5199554007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-30T16:52:05Z","expires_at":"2026-09-29T13:32:21.392166Z","created_at":"2026-07-31T14:02:19.892066Z","updated_at":"2026-08-30T13:32:21.533253Z","company_name":"Together AI","company_slug":"together-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=together.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/426da38a-255b-4b18-aa49-edd706e59a31"},{"id":"729a7b16-2793-4b11-aff6-a0af6753962e","company_id":"28040a6c-6f94-41a4-b15a-f2e4520188ff","title":"AI Evaluation Engineer","slug":"ai-evaluation-engineer-bacea6f4","description":"About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. \n Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. \n Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. \n Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. \n We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. \n We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . \n Your role As an AI Evaluation Engineer, you'll be an integral part of our AI Evaluation team, owning evaluation coverage for Dialpad's Agentic AI systems alongside our existing evaluation lead. A key focus will be co-owning LLM-judge metric development and calibration, scenario and benchmark dataset curation, and structured error analysis to support release-readiness decisions for our agentic voice and chat solutions. \n This position reports to the manager of the AI Evaluation team and has the opportunity to be based in our Vancouver office. \n What you’ll do  \n \n You will design and execute validation strategies for agentic, NLP, and speech workflows across staging, beta, and release candidates. \n You will build, run, and improve regression evaluations, A/B comparisons, and red teaming analyses to determine whether product and model changes are ready to move forward. \n You will co-own LLM-judge metric development, calibration, and prompt refinement across evaluation dimensions. \n You will create, configure, and monitor data annotation jobs to keep evaluation and calibration datasets fed on schedule. \n You will develop and maintain QA tooling, notebooks, and pipeline components that make recurring evaluations scalable and reusable across teams. \n You will investigate bugs, triage issues, and decide whether problems should become engineering escalations, test set additions, or follow-up analysis. \n You will collaborate with cross-functional teams, including applied science, engineering, and Product QA. \n \n Skills you’ll bring   \n \n Bachelor's or Master's degree in Computer Science, Software Engineering, Computational Linguistics, or a related field. \n 3+ years of experience in QA, test engineering, model evaluation, or applied ML quality for AI-driven products. \n Experience designing structured test strategies across manual and automated workflows. \n Comfort working with complex AI systems such as speech, NLP, LLM, or agentic products. \n Experience working with evaluation datasets, gold sets, adversarial test sets, or benchmark creation for AI systems. \n Strong analytical skills for investigating failures, comparing outputs, and identifying actionable quality patterns. \n Experience collaborating with cross-functional technical teams and communicating clearly through documentation and reporting. \n For exceptional talent based in Ontario, Canada  the target base salary range for this position is posted below. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the target range for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in Ontario role postings reflect the base salary only, and do not include bonus, equity, or benefits. \n Ontario Salary Range\n $96,000 — $116,250 CAD \n Why Join Dialpad \n \n Work at the center of the AI transformation in business communications \n Build and ship agentic AI products that are redefining how companies operate \n Join a team where AI amplif","salary_min":96000,"salary_max":116250,"location":"Kitchener, Canada","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["fine-tuning","alignment","nlp","llm","agents","evaluation"],"apply_url":"https://job-boards.greenhouse.io/dialpad/jobs/8642915002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-23T14:02:57Z","expires_at":"2026-09-29T13:50:48.916615Z","created_at":"2026-07-24T14:20:46.836616Z","updated_at":"2026-08-30T13:50:49.048491Z","company_name":"Dialpad","company_slug":"dialpad","company_logo_url":"https://www.google.com/s2/favicons?domain=dialpad.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/729a7b16-2793-4b11-aff6-a0af6753962e"}],"page":1,"per_page":20,"total":286,"total_is_exact":true,"total_pages":15}