{"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":"9b894a7b-e6ce-485c-b095-970a736af6dc","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Machine Learning Engineer, New Verticals Agentic Foundations","slug":"senior-machine-learning-engineer-new-verticals-agentic-foundations-a3f3a5d5","description":"About the Team\n Agentic Foundations, part of New Verticals ML, builds the core AI/ML intelligence that powers high-quality, scalable agents at DoorDash, and proves it through flagship agent experiences such as the Ask grocery assistant. We operate as a closed loop: new models, evals, and representations make our agents better, and real-world agent usage surfaces the gaps that drive our next foundations work. \n About the Role\n We’re looking for a Senior Machine Learning Engineer to join Agentic Foundations with a primary focus on Vertical Agent Development. You will own the continuous improvement of our flagship agents, starting with the Ask Assistant, using an eval-driven loop to make them faster, more cost-efficient, and more reliable for millions of customers. You will also help us bring this approach to new agentic experiences for Merchants and Dashers, turning promising ideas into production-ready agents.\n This is a chance to work at the intersection of LLMs, agents, post-training, and evals on problems that ship. You will partner closely with engineers working on agentic memory, agent-compatible product representations, and post-training of small language models (SLMs), so that what we learn from production agents feeds directly back into our foundations, and what we build there makes our agents better.\n You will report into the engineering lead on our New Verticals AI/ML team. We expect this role to be hybrid with some time in-office and some time remote.\n You’re excited about this opportunity because you will…\n \n Raise the quality of our Consumer agents: build and refine our eval harness-optimization loop to pinpoint failure modes, then iterate on prompts, tools, skills, and context, and measure the impact on real customer tasks.\n Find the best balance of quality, latency, and cost: run rigorous experiments, including fine-tuning open-weights models and deploying small language models (SLMs) where they can replace or augment larger LLMs.\n Launch new agents: take agentic opportunities for Merchants and Dashers from early exploration to production.\n Turn foundations into product impact: work with teammates on agentic memory, agent-compatible product representations, and post-training SLMs for steerable generative recommendation, and bring those capabilities into production agents.\n Shape the roadmap: partner with engineering, product, and business leaders to define an ML-driven strategy for our fast-growing grocery and retail delivery business.\n \n We’re excited about you because you have…\n \n 3+ years of industry ML experience, including hands-on work building and shipping LLM-based agents (tool use, context management, prompting, guardrails) and improving them with evals and data\n Experience with post-training or fine-tuning of open-weights models (e.g., SFT, preference optimization, or RL), ideally including small language models, and sound judgment on quality, latency, and cost trade-offs\n Strong foundation in NLP and machine learning, with proficiency in Python and frameworks such as PyTorch or TensorFlow\n M.S. or PhD in Computer Science, Statistics, Math, or another quantitative field, or equivalent practical experience, plus a collaborative, growth-minded approach and a drive for measurable impact\n Compensation \n The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.\n In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\n DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.\n To learn more about our benefits, visit our careers page here .\n See below for paid time off details:\n \n For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).\n \n The national base pay range for this position within the United","salary_min":167800,"salary_max":246800,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["tensorflow","llm","fine-tuning","agents","cloud","pytorch","nlp","healthcare"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8279145","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-13T17:38:05Z","expires_at":"2026-11-13T17:03:28.711787Z","created_at":"2026-10-14T15:25:31.355292Z","updated_at":"2026-10-14T17:03:28.714838Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9b894a7b-e6ce-485c-b095-970a736af6dc"},{"id":"943a5e5f-5b9a-4c60-ae1f-a9319c87ec0e","company_id":"4bc4e268-7a05-4a65-a162-1688af546f7e","title":"Senior Machine Learning Programmer","slug":"senior-machine-learning-programmer-dd417989","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 PROGRAMMING - 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 What You'll Do \n You will work with our team of applied research programmers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create state-of-the-art tools to support game developers in our ecosystem with a focus on bots (trained gameplay agents, intelligent NPCs, companions, world modeling), as well as automation of a number key areas (including moderation, security, and QA testing). You will be responsible for the design, implementation and deployment of production-ready machine learning models that can be integrated in our ecosystem.\n In this role, you will \n \n Create and deliver production-ready, scalable and high-quality machine learning models and associated algorithms that can make actions in game environments\n Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap\n Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones\n \n What we're looking for \n \n PhD in Computer Science, Mathematics or related field, or 3+ years of relevant industry experience\n Experience creating / applying machine learning algorithms for action modeling of bots behavior, vision-based or language-instructed, and deploying them as production-level systems in-game\n Expert, hands-on knowledge of:\n \n Deep learning, incl. but not limited to applications in the gaming industry\n Foundational models and vision and/or language, especially vision-language-action models, reinforcement learning agents, incl. local deployment and model post-training of open weights models\n Reinforcement learning, incl. experience with agentic systems, reward design, policy optimisation, evaluation, and building scalable training environments for agents\n Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch)\n \n Experience with working collaboratively with other developers, following a flexible/agile/lean approach\n \n This role is open to multiple locations across North America \u0026 Europe (including NYC). \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 $232,666 — $341,243 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 remarkable games, we strive to build teams of world-class talent.\n Like what you hear? Come be a part of something Epic! \n Epic Games deeply values diverse teams and an inclusive work culture, and we are proud to be an Equal Opportunity employer. Learn more about our Equal Employment Opportunity (EEO) Policy here .\n Note to Recruitment Agencies: Epic does not accept any unsolicited resumes or approaches from any unauthorized third party (including recruitment or placement agencies) (i.e., a third party with whom we do not have a negotiated and validly executed agreement). We will ","salary_min":232666,"salary_max":341243,"location":"BLANK,BLANK,Multiple Locations","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","pytorch","deep-learning","reinforcement-learning","nlp","computer-vision","machine-learning"],"apply_url":"https://epicgames.com/careers/jobs/6221662004?gh_jid=6221662004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T19:46:26Z","expires_at":"2026-11-13T17:02:44.874623Z","created_at":"2026-10-14T15:24:47.963173Z","updated_at":"2026-10-14T17:02:44.878058Z","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/943a5e5f-5b9a-4c60-ae1f-a9319c87ec0e"},{"id":"58d65f8c-9bfe-4e0f-8026-f55da835720b","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Staff Machine Learning Engineer","slug":"staff-machine-learning-engineer-9c39e036","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n Staff Machine Learning Engineer, CX Intelligence \n  \n CEE Intelligence (CEEI) is the ML and intelligence layer for Coinbase's customer engagement ecosystem, building customer intelligence, evaluation systems, routing and classification models, safety guardrails, and decisioning capabilities that power Help Center, chat, voice, agent tooling, and other customer support runtimes. As a Staff Machine Learning Engineer, you'll lead the design and delivery of production ML systems across the org, shaping technical strategy, building scalable intelligence capabilities, and partnering with product and engineering stakeholders to improve resolution quality, automation coverage, safety, and customer experience. What you'll do: \n \n Own the design and delivery of production ML systems, applying LLMs, deep learning, graph neural networks, and classical ML techniques to solve complex customer experience problems.\n Partner with leadership and cross-functional stakeholders to define strategic roadmaps and translate vision into quarterly execution plans with measurable outcomes.\n Lead high-impact ML projects end-to-end, from architecture through production, managing priorities, risks, and dependencies.\n Build scalable, secure, and reliable ML systems, evaluation pipelines, and data workflows using high-quality, well-tested Python code.\n Mentor engineers and establish team-wide standards for design, testing, observability, and operational excellence.\n Drive design reviews covering security, responsible AI, model quality, and architectural integrity, improving reliability, scalability, and latency across the stack.\n \n Required Skills and Experience: \n \n 8+ years of experience in machine learning and software engineering, with proven success building, scaling, and maintaining production ML systems, data platforms, or analytical services.\n Hands-on expertise with one or more of LLMs, deep learning, graph neural networks, gradient-boosted trees, or regression, combined with strong knowledge of NLP, information retrieval, data mining, or advanced statistics.\n Strong Python skills with demonstrated ability to write maintainable, highly tested production code for ML services.\n Experience mentoring engineers and raising technical standards across a team or organization, including leading design reviews and influencing technical and non-technical stakeholders.\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n \n Job #: P77568\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $218,025 — $256,500 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":218025,"salary_max":256500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["generative-ai","llm","nlp","deep-learning","search","machine-learning"],"apply_url":"https://www.coinbase.com/careers/positions/8267151?gh_jid=8267151","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T19:31:10Z","expires_at":"2026-11-13T16:58:01.54146Z","created_at":"2026-10-14T15:21:41.463785Z","updated_at":"2026-10-14T16:58:01.544331Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/58d65f8c-9bfe-4e0f-8026-f55da835720b"},{"id":"70e145b8-5b41-4b48-a424-a088b204b2a6","company_id":"b467c425-56b3-40ce-826a-e603e82a08bd","title":"[2027] Senior Machine Learning Engineer - PhD Early Career","slug":"2027-senior-machine-learning-engineer-phd-early-career-b6d69cf2","description":"Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.  \n At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.  \n A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. \n At Roblox, we believe advanced research belongs in production, driving core algorithmic advances at a global scale. In this role, you’ll own high-impact projects end-to-end, from initial ideation to production deployment and academic publication, while solving complex, high-dimensional challenges at world-scale concurrency. \n Your expertise, across research areas including Computer Vision and Graphics, multimodality, NLP, or recommendation systems, will directly shape the experience for millions of daily active users. Come build the AI-driven infrastructure powering the future of immersive entertainment.\n You Will \n \n Prototype and implement advanced AI and machine learning solutions that drive core platform features and innovation at scale.\n Develop and deploy cutting-edge models (e.g., deep learning, generative AI, multimodal architectures) to solve complex, high-impact technical challenges.\n Collaborate with applied researchers, engineers, and product teams to translate advanced research concepts into production-ready systems.\n Translate complex research into scalable, robust infrastructure that directly impacts hundreds of millions of daily active users.\n Work backward from user and product needs to architecture, and deliver ML solutions that improve platform engagement, safety, and content ecosystem growth.\n \n You Have \n \n Possess or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.\n Deep expertise and curiosity in a relevant technical domain, such as deep learning, computer vision, NLP, reinforcement learning, or distributed systems.\n Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.\n A strong research track record, evidenced by multiple publications and presentations in rigorous peer-reviewed venues.\n \n You may redact age, date of birth, and dates of attendance/graduation from your resume.\n As you apply, you can find more information about our process by signing up for Speak_. You'll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.\n For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page .\n Annual Salary Range\n $196,750 — $243,290 USD \n Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).\n Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.\n For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.","salary_min":196750,"salary_max":243290,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["computer-vision","deep-learning","distributed-systems","generative-ai","nlp","reinforcement-learning","machine-learning"],"apply_url":"https://careers.roblox.com/jobs/8242623?gh_jid=8242623","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T16:05:13Z","expires_at":"2026-11-13T17:02:53.108743Z","created_at":"2026-10-14T15:24:56.108637Z","updated_at":"2026-10-14T17:02:53.113421Z","company_name":"Roblox","company_slug":"roblox","company_logo_url":"https://www.google.com/s2/favicons?domain=roblox.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/70e145b8-5b41-4b48-a424-a088b204b2a6"},{"id":"62316960-4081-4d09-883a-e1356f1a8463","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Senior AI Analyst, People Digital Solutions","slug":"senior-ai-analyst-people-digital-solutions-c64475e7","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n The People Operations \u0026 Digital Solutions team \n The People Operations \u0026 Digital Solutions team shapes the future of employee support at Okta through innovative technology, intelligent knowledge management, and automated self-service experiences. Reporting to the Senior Director, People Operations \u0026 Digital Solutions, this team collaborates closely with People Operations, Total Rewards, Recruiting, IT, Learning, and Knowledge Management to enhance digital support across the enterprise.\n The Senior AI Analyst opportunity \n We are seeking an experienced Senior AI Analyst with a strong background in ServiceNow and Analytics to help train, evaluate, and improve AI models and AI-powered enterprise solutions. The ideal candidate will combine hands-on ServiceNow knowledge, data and analytics expertise, and strong communication skills to create high-quality training data, evaluate AI outputs, and translate business and technical requirements into effective AI training scenarios. This is a high-impact role responsible for improving how employees interact with AI while enabling support teams through intelligent knowledge management and training.\n As the subject matter expert for our AI solutions, you will analyze conversational insights, optimize AI performance, and ensure AI assistants deliver accurate, relevant, and trusted responses. You'll own the training and continuous improvement of AI-powered experiences—including an employee support chatbot, Agentic Coach, and future AI assistants—while partnering with cross-functional teams to enhance knowledge, self-service, and employee support.\n What you’ll be doing  \n \n Train, test, and evaluate AI-powered assistants, chatbots, and agentic AI solutions to ensure accurate and reliable employee experiences.\n Design and optimize prompts, conversational flows, intents, responses, and training scenarios across enterprise support platforms.\n Evaluate AI outputs for accuracy, relevance, completeness, tone, and consistency while identifying and mitigating hallucinations, response gaps, or misinformation.\n Monitor and analyze AI performance metrics such as containment, resolution, user satisfaction, engagement, and escalation rates; identify trends, emerging intents, knowledge gaps, and opportunities for automation from conversational data.\n Apply ServiceNow knowledge to translate complex business processes into intuitive conversational scenarios, training data, and evaluation criteria; collaborate with ServiceNow administrators, developers, analysts, and business stakeholders to identify automation opportunities.\n Create and maintain AI training materials, test cases, evaluation criteria, and sample conversations; partner with Knowledge Management teams to improve content quality, discoverability, and AI readiness; keep materials current as products, processes, and policies evolve.\n Support testing and rollout of new AI capabilities and enhancements; provide insights and recommendations based on AI performance, user feedback, and analytics to drive continuous improvement across the People Organization.\n Stay current with developments in generative AI, prompt engineering, conversational AI, agentic AI, and responsible AI; contribute ideas that improve employee self-service and digital support experiences.\n \n What you’ll bring to the role \n \n Experience in AI training, prompt engineering, conversational design, NLP, or AI optimization within employee or customer support environments.\n Proven experience training, evaluating, and optimizing AI models, conversational agents, or LLM-powered assistants, including agentic AI solutions.\n Strong understanding of prompt engineering, AI evaluation, model optimization, and responsible AI practices.\n Demonstrated ability to analyze conversational data and performance metrics to drive measurable improvements.\n Working knowledge of ServiceNow or a similar enterprise service-management platform.\n Strong analytical skills and experience with tools such as SQL, Excel, Power BI, Tableau, or ServiceNow Analytics.\n Experience with enterprise conversational AI platforms, knowledge management systems, or AI-enabled search technologies.\n Excellent written and verbal communication skills with the ability to translate technical and business requirements into clear, user-focused content and influence cross-functional stakeholders.\n Understanding of knowledge management, digital employee support, and omnichannel service experiences.\n \n A","salary_min":108000,"salary_max":149000,"location":"Bellevue, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","generative-ai","llm","nlp","fine-tuning"],"apply_url":"https://www.okta.com/company/careers/opportunity/8257554?gh_jid=8257554","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-08T13:19:08Z","expires_at":"2026-11-13T16:58:07.274356Z","created_at":"2026-10-14T15:21:47.277821Z","updated_at":"2026-10-14T16:58:07.277552Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/62316960-4081-4d09-883a-e1356f1a8463"},{"id":"25cc098c-d5a9-4722-8570-cdb9d8c94f57","company_id":"63bced38-3605-4e57-99f3-e213b2d40bf3","title":"Data Scientist II","slug":"data-scientist-ii-cdd4036b","description":"Data Scientist II, Cohere Health, Inc., Boston, Massachusetts (Remote) \n Duties: Gather business requirements and apply trend analysis to identify actionable insights using analytic tools. Analyze healthcare claims and authorization data to identify outliers, interpret patterns, and assess trends and opportunities. Apply large language models (LLMs), stochastic optimization methods, and related technologies to support decision-making. Monitor industry trends, regulatory changes, and emerging fraud schemes to support detection strategy development, maintain methodology documentation, and present findings to leadership. Train, fine-tune, and implement LLMs and deep learning models for tasks such as anomaly detection, classification, and automated analysis of security-related or operational data. Analyze datasets to assess expected impacts and return on investment, including effects on medical expense, administrative cost, and clinical outcomes. Develop data models, algorithms, and simulations to support analytical objectives. Build visualizations and dashboards to communicate analytical findings and support business workflows.\n This is a fully remote position and may be performed from anywhere within the United States. Occasional travel to company headquarters in the U.S. for onboarding, team meetings, and company events may be required.\n Requirements:\n Must have a Master’s degree in Data Science, Statistics, Biostatistics or related field (willing to accept foreign education equivalent) and 36 months of experience as Analyst or related position analyzing datasets.\n Must possess three (3) years of experience (may be gained concurrently with above experience) in the following skills:\n \n Analyzing healthcare datasets, including EMR/EHR data, medical and pharmacy claims data, and Social Determinants of Health (SDoH) data;\n Performing data quality analysis to identify data quality issues, gaps, or inconsistencies;\n Building scalable AWS Airflow pipelines to ingest, integrate, and transform terabytes of data using Python and PySpark and AWS S3 storage, and accelerate business decision-making in AWS Sagemaker; \n Utilizing trend identification and data analysis methods such as regression analysis and outlier detection model in python, spark and sql.;\n Building and implementing models, creating algorithms, and running simulations;\n Developing Tableau visualization and partnering with product owners and stakeholders to drive enterprise-level solutions that integrate data science into business workflows; \n Developing NLP, LLMs (extractive and generative), fine-tuning, and LLM model development.\n \n Salary range is $137,000.00 to $161,000.00 per year for a 40-hour work week.\n #LI-DNI\n -\n #BI-DNI\n -","salary_min":137000,"salary_max":161000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["healthcare","nlp","fine-tuning","cloud","llm","deep-learning","data-science"],"apply_url":"https://job-boards.greenhouse.io/coherehealth/jobs/8005450003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-05T19:10:55Z","expires_at":"2026-11-13T16:56:47.541154Z","created_at":"2026-10-14T15:20:32.691553Z","updated_at":"2026-10-14T16:56:47.544068Z","company_name":"Cohere Health","company_slug":"cohere-health","company_logo_url":"https://www.google.com/s2/favicons?domain=coherehealth.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/25cc098c-d5a9-4722-8570-cdb9d8c94f57"},{"id":"2dfdf022-1baf-4133-a9ec-68fda0e96567","company_id":"1bb3dab4-a54d-456f-bfd6-ad41828ae177","title":"Senior Director, Platform Products","slug":"senior-director-platform-products-465c93a8","description":"Head of Platform Products \n SD Product, Suki for Partners \n Why Suki — and Why Now \n Suki is creating a new category in health technology: the AI-powered digital assistant for healthcare. Our mission is simple but profound—give time back to clinicians so they can focus on what matters most: caring for patients.\n Today, doctors spend hours navigating complex electronic health record (EHR) systems—modern versions of paper charts that are often unintuitive, fragmented, and time-consuming. Suki changes that. Clinicians using Suki already spend 70% less time on administrative work, and we’re just getting started.\n Our platform is the foundation of everything we do. As we scale AI-powered capabilities across voice, ambient, and enterprise experiences—and extend them to health system partners, EHR ecosystems, and third-party developers—we need a seasoned platform product leader to define and drive the next generation of our technical platform strategy.\n The Role \n As Head of Platform Products, you will own the product vision, strategy, and roadmap for Suki’s core platform—the APIs, services, and integration layers that enable external partners to build on top of our technology.\n You will lead a team of platform product managers and serve as a strategic partner to Engineering, Commercial, and executive leadership. Your work will determine how Suki’s AI, speech, and clinical intelligence capabilities are architected, scaled, and delivered to the broader healthcare ecosystem.\n This is a rare opportunity to shape the platform that underpins an AI-first healthcare company—and to set a new standard for how health technology platforms are built and scaled.\n What You’ll Do \n Define Platform Vision \u0026 Strategy \n \n Own and drive a clear, compelling multi-year platform product strategy that enables Suki’s product portfolio and ecosystem growth\n Define the platform’s service architecture, API strategy, and extensibility model to support current products and future innovation\n Translate complex AI/ML, NLP, and speech capabilities into well-architected, reusable platform services\n \n Drive Interoperability \u0026 Health Data Strategy \n \n Own the strategy for integrations including EHR (Athena and others), ensuring deep, reliable, and scalable connectivity\n Define the approach to health data standards (FHIR, HL7, CDA) and ensure the platform is built for healthcare-grade interoperability\n Partner with compliance and security teams to maintain HIPAA compliance, SOC 2 certification, and enterprise-grade data governance across the platform\n \n Scale AI \u0026 ML Platform Capabilities \n \n Work closely with AI/ML leadership to productize core capabilities—ambient AI, clinical NLP, medical speech recognition, and generative AI—as scalable platform services\n Enable rapid experimentation and deployment of new AI capabilities across product surfaces\n \n Build for the Ecosystem \n \n Define and execute the developer platform and partner integration strategy, including APIs, SDKs, documentation, and developer experience\n Work with business development and partnerships teams to identify and enable high-value platform use cases for health systems, EHR vendors, and third-party developers\n Build the foundation for a platform ecosystem that creates compounding value for Suki and its partners\n \n Be a Strategic Product Partner \n \n Partner closely with the Chief Product Officer, Engineering leadership, and Commercial leadership to align platform investments with company strategy and product roadmap\n Ground platform decisions in data, customer insights, technical feasibility, and business impact\n Drive prioritization and trade-off decisions across competing platform demands from internal teams and external partners\n \n Build and Scale a World-Class Team \n \n Lead, mentor, and grow a high-performing platform product management team\n Foster a culture of technical excellence, customer empathy, accountability, and impact\n Identify and close gaps in skills, tools, processes, and operating models as the platform organization scales\n \n What We’re Looking For \n \n 12+ years of product management experience, with 5+ years in senior/leadership roles owning platform, infrastructure, or developer-facing products\n Deep expertise in platform product management: APIs, developer experience, data platforms, integration architectures, and service-oriented systems\n Strong background in healthcare technology, with hands-on experience navigating EHR ecosystems, health data standards (FHIR, HL7), and regulatory requirements (HIPAA, SOC 2)\n Experience productizing AI/ML capabilities at scale—ideally in NLP, speech, or applied clinical AI\n Proven track record of building and scaling platform product teams in high-growth, product-led organizations\n Technically fluent: comfortable engaging deeply with engineering and data science teams on architecture, systems design, and technical trade-offs\n Strong analytical and strategic thinking skills, with the ability ","salary_min":300000,"salary_max":350000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","speech","nlp","healthcare"],"apply_url":"https://www.suki.ai/open-positions?gh_jid=7701264003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-05T18:39:48Z","expires_at":"2026-11-13T16:59:13.387627Z","created_at":"2026-10-14T15:22:45.229335Z","updated_at":"2026-10-14T16:59:13.390591Z","company_name":"Suki","company_slug":"suki","company_logo_url":"https://www.google.com/s2/favicons?domain=suki.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2dfdf022-1baf-4133-a9ec-68fda0e96567"},{"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":"Build AI contracting at enterprise scale. Ship it fast.\n\nIronclad is building AI on one of the most consequential datasets in enterprise software: over 2 billion contracts across thousands of the world's largest organizations. Contracts run every dollar, deal, and business relationship on the planet, and the AI transformation of this space is still largely uncharted. Engineers here are building agentic solutions to problems that haven't been solved yet, in a category that's still being defined. The feedback loop is short, the data is rich, and the people closest to the work are the ones deciding what gets built next. That ability to deliver impact quickly is why the the companies at the forefront of AI choose Ironclad to manage their contracts.\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 ca","salary_min":220000,"salary_max":270000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["rag","llm","nlp","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":"2026-10-05T15:18:25.532Z","expires_at":"2026-11-13T16:58:49.178687Z","created_at":"2026-08-26T13:41:23.863704Z","updated_at":"2026-10-14T16:58:49.181975Z","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":"e0be16b1-242b-4a96-b22e-736f0755cae8","company_id":"5a1ac926-3bb4-40bb-b952-7dc959ae1820","title":"Tech Lead Manager, Machine Learning, Growth and Marketing   ","slug":"tech-lead-manager-machine-learning-growth-and-marketing-527e3a43","description":"About the Role \n Chime’s Data Science and Machine Learning team is building models, services, and platforms that transform how millions of users manage and grow their financial lives. We are looking for a hands-on Tech Lead Manager with deep technical expertise in machine learning and data science, particularly within the Growth and Marketing domain. Beyond technical proficiency, we value creativity, user empathy, and strong collaboration. \n As a Tech Lead Manager within our Growth and Marketing team, you will lead a talented group of data scientists and machine learning engineers to develop innovative growth and marketing models. These models will provide critical insights into acquiring, retaining and growing Chime members, broaden access to credit, and ensure financial inclusivity. You will play a pivotal role in creating innovative, ground-up products while driving the development of cutting-edge acquisition and retention models and solutions. If you are passionate about marketing, growth, customer acquisition and retention models, this role could be a great fit for you. \n In this role, you can expect to \n \n Lead and inspire a high-performing team of data scientists and ML engineers, ensuring the successful development and deployment of machine learning solutions for customer acquisition, conversion and retention. \n Drive strategic direction for ML initiatives in marketing, engagement, and growth by identifying opportunities where AI/ML can optimize our customer funnel. \n Oversee the end-to-end development of machine learning models such as lifetime value prediction, churn risk modeling, customer segmentation, marketing attribution, referral recommendations, and personalized communications. \n Collaborate cross-functionally with marketing, product, growth, and engineering teams to align machine learning initiatives with business objectives. \n Leverage transactional and behavioral data to enhance customer targeting, optimize acquisition spend, and improve retention strategies. \n Establish ML best practices, including model development, validation, deployment, and monitoring, ensuring scalability and business impact. \n Advocate for a data-driven culture, partnering with business leaders to drive strategic decisions through experimentation and predictive analytics. \n Stay ahead of industry trends, bringing cutting-edge AI/ML techniques into our marketing and growth strategies. \n \n To thrive in this role, you have \n \n 7+ years of experience developing machine learning models for marketing and growth, from inception to production, with a focus on customer acquisition, engagement, and retention. \n 5+ years of experience leading data science teams, with a proven track record of mentoring, coaching, and driving impactful machine learning solutions. \n Strong expertise in marketing and growth analytics, including experience with customer segmentation, LTV modeling, churn prediction, referral systems, and multi-touch attribution. \n Deep understanding of AI/ML techniques, including classification, clustering, reinforcement learning, optimization, deep learning, and NLP for customer engagement. \n Hands-on experience deploying machine learning models in real-world production environments, integrating with marketing tech stacks and growth platforms. \n Strong product intuition with the ability to work iteratively in a fast-paced, cross-functional environment. \n M.S. or Ph.D. in Machine Learning, Computer Science, Statistics, or a related STEM field. \n Proficiency in Python and SQL, with experience in building ML pipelines and wrangling large-scale data. \n Experience with modern ML and data engineering technologies, such as AWS, Kafka, Airflow, Redis, MySQL, Postgres, Spark, Snowflake, Looker. \n Exceptional communication and stakeholder management skills, with the ability to partner effectively with marketing, growth, product, and engineering teams. \n \n #LI-DA1 #LI-Onsite \n Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.\n Wage Notice\n $199,000 — $275,000 USD \n A little about us \n At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. \n We're a team of problem solvers, dreamers, and builders with one ","salary_min":199000,"salary_max":275000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["nlp","deep-learning","payments","reinforcement-learning","data-engineering","machine-learning"],"apply_url":"https://boards.greenhouse.io/chime/jobs/8864214002?gh_jid=8864214002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-02T18:01:52Z","expires_at":"2026-11-13T17:03:12.47807Z","created_at":"2026-10-14T15:25:16.005996Z","updated_at":"2026-10-14T17:03:12.481159Z","company_name":"Chime","company_slug":"chime","company_logo_url":"https://www.google.com/s2/favicons?domain=chime.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e0be16b1-242b-4a96-b22e-736f0755cae8"},{"id":"966ace03-2145-430c-ba1e-b86655a2101e","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Master's University Grad Machine Learning Engineer 2027 (USA)","slug":"masters-university-grad-machine-learning-engineer-2027-usa-bfd4b4f4","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 With more than 640 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers help build personalized experiences to help Pinners create a life they love. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.\n By applying to this role, you will be considered for multiple roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process. \n This is a general posting for multiple roles open across our various ML teams. You will have the opportunity to work on a very large scope of problems in recommender systems, search, ads, ranking, natural language processing, graph representation learning, personalization, etc. \n As a Machine Learning Engineer at Pinterest, you’ll work on tackling new challenges in machine learning and artificial intelligence. As you kickstart your career at Pinterest, you’ll join our engineering teams as we maneuver through exponential growth and massive scale while building awesome products and features, creating visually rich experiences, spearheading the discovery problem, and pinpointing tomorrow’s engineering challenges. \n What you’ll do: \n \n Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems\n Collect, analyze, and synthesize findings from data and build intelligent data-driven model\n Write clean, efficient, and sustainable code\n Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search\n Design, build, and test models to predict engagement for notifications (push, emails, in-app notifications)\n Build content recommendation systems to power our push, email, and in-app notifications\n Work on state-of-the-art large-scale applied machine learning projects\n Scope and independently solve moderately complex problems\n \n What we’re looking for: \n \n Master's in Computer Science, ML, NLP, Statistics, Information Sciences or related field required\n Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)\n Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data\n Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)\n Proficiency with AI-native engineering, including the design of agent-friendly codebases.\n High degree of autonomy in learning new agent-first development tools.\n Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.\n Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.\n Experience in research and in solving analytical problems\n Strong communicator and team player. Being able to find solutions for open-ended problems.\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 may require you to be located near an office for in-person collaboration, and therefore may need to be located a commutable distance from one of our Pinterest offices. \n \n #LI-HYBRID \n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary","salary_min":146000,"salary_max":196000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["pytorch","tensorflow","computer-vision","search","nlp","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8140219","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-01T17:00:43Z","expires_at":"2026-11-13T16:57:51.091469Z","created_at":"2026-10-14T15:21:31.340179Z","updated_at":"2026-10-14T16:57:51.094368Z","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/966ace03-2145-430c-ba1e-b86655a2101e"},{"id":"c409314e-e707-469d-980c-8770d7b5d672","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"PhD University Grad Machine Learning Engineer (USA) ","slug":"phd-university-grad-machine-learning-engineer-usa-584220a7","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 With more than 640 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers help build personalized experiences to help Pinners create a life they love. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.\n By applying to this role, you will be considered for multiple roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process. \n This is a general posting for multiple roles open across our various ML teams. You will have the opportunity to work on a very large scope of problems in recommender systems, search, ads, ranking, natural language processing, graph representation learning, personalization, etc. \n  \n As a Machine Learning Engineer at Pinterest, you’ll work on tackling new challenges in machine learning and artificial intelligence. As you kickstart your career at Pinterest, you’ll join our engineering teams as we maneuver through exponential growth and massive scale while building awesome products and features, creating visually rich experiences, spearheading the discovery problem, and pinpointing tomorrow’s engineering challenges. \n What you’ll do: \n \n Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems\n Collect, analyze, and synthesize findings from data and build intelligent data-driven model\n Write clean, efficient, and sustainable code\n Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search\n Design, build, and test models to predict engagement for notifications (push, emails, in-app notifications)\n Build content recommendation systems to power our push, email, and in-app notifications\n Work on state-of-the-art large-scale applied machine learning projects\n Scope and independently solve moderately complex problems\n \n What we’re looking for: \n \n PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field required\n Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)\n Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data\n Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)\n Proficiency with AI-native engineering, including the design of agent-friendly codebases.\n High degree of autonomy in learning new agent-first development tools.\n Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.\n Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.\n Experience in research and in solving analytical problems\n Strong communicator and team player. Being able to find solutions for open-ended problems.\n Preferred Qualifications: \n \n Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields\n Interest in research and in applying ML to impactful real-world problems on the Pinterest product\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 may require you to be located near an office for in-person collaboration, and therefore may need to be located a commutable distance from one of our Pinterest offices.\n \n   \n #LI-HYBRID \n #LI-EB1\n At Pinte","salary_min":174078,"salary_max":229044,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["search","nlp","computer-vision","pytorch","tensorflow","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8140363","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-01T17:00:35Z","expires_at":"2026-11-13T16:57:51.109891Z","created_at":"2026-10-14T15:21:31.35309Z","updated_at":"2026-10-14T16:57:51.113365Z","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/c409314e-e707-469d-980c-8770d7b5d672"},{"id":"0f46b7b7-9959-4d88-96d9-c6227e64bb30","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Research Scientist - Human-AI Systems","slug":"research-scientist-human-ai-systems-eefa08a8","description":"About Snorkel \n Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes.  Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n \n \n We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input. Working with domain experts, academic partners, customers, and our product and engineering teams, you’ll scale these pipelines to target frontier model performance gaps and expand data and environment diversity. Your work will amplify human knowledge and judgement, enabling experts to create and refine data and agentic environments that strengthens Snorkel’s position as the frontier data lab.\n This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems.\n Location: San Francisco, New York City,  OR REMOTE \n Main Responsibilities \n \n Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation.\n Design and run rigorous experiments to validate proof-of-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communicate findings.\n Partner with engineering, data operation, domain experts, and customers to turn research prototypes into reliable production workflows.\n Work directly with domain experts to design and test workflows that help them author, review, and refine data and environments.\n Work cross-functionally with data operations, product, and engineering to surface research findings that inform the company roadmap. \n Stay at the frontier of research in data and agentic environment creation and bring best practices into Snorkel's workflows.\n Represent Snorkel's research externally through publications, blog posts, conference talks, and customer engagements that advance the conversation around data-centric AI.\n \n Preferred Qualifications \n \n Strong research background in AI, machine learning, NLP, LLMs, or related fields, with experience developing and evaluating new methods.\n Experience building environments for AI agents in automated research, computer use, coding, or professional domain workflows.\n Experience with one or more of synthetic data generation, human in the loop workflows, reinforcement learning, agent environments, or model evaluation.\n Strong experimental design skills, including defining hypotheses and conducting ablations.\n Experience with software engineering best practices (e.g., clean coding, modular design, version control).\n Ability to collaborate with domain experts and translate their knowledge into concrete tasks, evaluation criteria, and repeatable workflows.\n Comfort with rapid iteration, ambiguous research questions, and moving ideas from experimentation into production.\n Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.\n \n \n  \n Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.\n Salary range(s) for this role\n $200,000 — $375,000 USD \n Be Your Best at Snorkel \n Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.\n Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, perfor","salary_min":200000,"salary_max":375000,"location":"New York, NY","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["reinforcement-learning","llm","nlp","agents","research"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6208895004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-25T20:17:42Z","expires_at":"2026-11-13T16:55:33.51421Z","created_at":"2026-10-14T15:19:23.633811Z","updated_at":"2026-10-14T16:55:33.516936Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0f46b7b7-9959-4d88-96d9-c6227e64bb30"},{"id":"e06f09a9-08e9-49e5-a5b6-c6a9742a36c5","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Machine Learning Engineer, Search Quality","slug":"machine-learning-engineer-search-quality-5dc8a594","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. You'll be 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 About the Role: \n  \n Glean is looking for engineers to help build the world’s best search and assistant product for work. Our engineers work on a range of systems across the stack, including query understanding, document understanding, domain-adapted language models, natural language question-answering, evaluation, and experimentation. We interact regularly with customers, deeply understand their pain points, and use whatever tool is necessary, simple or complex, to solve their problems. \n  \n You will:  \n \n \n Invent new signals to improve the personalization of our search engine \n Train a model to capture interactions between signals in our ranking system \n Design smarter ways to domain-adapt language models to each customer’s corpus \n Discover new ways of combining LLMs with search engines to answer complex questions \n Write robust code that’s easy to read, maintain, and test \n Mentor more junior engineers, or learn from battle-tested ones \n \n About you: \n \n \n 2+ years of experience \n BA/BS in computer science, math, sciences, or a related degree \n Experience working with search, recommendation, natural language processing, or other large systems involving machine learning \n Strong analytical skills and ability to work with data \n Proven ability to design, build, and ship production-ready models \n Proficiency in your ML framework of choice \n Strong coding skills (Python, Go, Java, C++, ...) \n Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company is a must \n A proactive and positive attitude to lead, learn, troubleshoot and take ownership of both small tasks and large features \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 $140,000 - $265,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. \n  \n We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. \n  \n We’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis","salary_min":140000,"salary_max":265000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["agents","search","nlp","cloud","llm","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4738120005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-25T18:50:37Z","expires_at":"2026-11-13T16:55:35.144081Z","created_at":"2026-10-14T15:19:25.279367Z","updated_at":"2026-10-14T16:55:35.147075Z","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/e06f09a9-08e9-49e5-a5b6-c6a9742a36c5"},{"id":"7ef52fd3-3cc0-4c90-9f0a-f64a1b317d4e","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Staff Machine Learning Engineer (Modeling), Support","slug":"staff-machine-learning-engineer-modeling-support-741ead08","description":"Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone. Join us.\n The Role \n Block's Support ML Modeling team is a central driver of innovation in customer support experiences across our entire ecosystem—including Cash App, Square, and other business units. We are dedicated to advancing the state of intelligent, automated support through machine learning and generative AI. From customer-facing chatbots to smart internal tools for agents, our team builds high-impact, scalable systems that improve support quality, efficiency, and accessibility.\n We're building the future of support at Block: one powered by AI, voice interfaces, and smart automation. We're looking for candidates with a passion for intelligent systems, practical ML experience, and a desire to build product-driven solutions. Our ideal candidate is a leader in the field, with a proven track record of building ML systems that can accelerate our ability to scale our conversational AI initiatives. \n You Will \n \n Lead the end-to-end delivery of multiple ML initiatives, from planning and design through rollout, documentation, and long-term maintenance\n Partner strategically with risk, product, engineering, design, and operations leaders to define and drive long term ML roadmaps, informed by domain expertise and industry trends\n Guide the team’s direction, identifying new ML/AI opportunities and advising leadership on strategic tradeoffs and opportunities\n Drive R\u0026D efforts exploring next-generation chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference\n Design, deploy, and maintain ML models powering conversational agents including support chatbots across Cash App, Square, and other Block products\n Develop ML-powered tools and real time recommendation systems that enhance support agent effectiveness and customer outcomes\n Act as the technical representative for your team’s systems and programs, clearly communicating work and results to stakeholders, cross-functional partners, and external audiences\n \n You Have \n \n 10+ years of experience in machine learning, applied AI, or product ML roles, with deep technical expertise\n Demonstrated leadership capabilities, with the ability to influence and align cross-functional teams while directly shaping the work of peers through communication, context sharing, and technical guidance\n A track record of delivering organizational wide impact, shaping systems, frameworks, or initiatives that raise the bar across multiple teams or functions\n Proven ability to ship end to end ML features from problem framing through deployment and long-term maintenance\n Demonstrated experience with language models, dialog systems, or generative AI in production\n Strong foundation in NLP, deep learning, or ML infrastructure best practices.\n Excellent communication skills, with the ability to represent the team’s work to leadership and stakeholders\n Enthusiasm for R\u0026D and pushing the boundaries of applied AI to transform conversational systems\n \n Technologies We Use and Teach \n \n Python, PyTorch, TensorFlow, or JAX\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 \n \n \n Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.\n ","salary_min":276800,"salary_max":415200,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","fine-tuning","generative-ai","deep-learning","cloud","nlp","pytorch","tensorflow"],"apply_url":"http://block.xyz/careers/jobs/5431987008?gh_jid=5431987008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-22T21:19:49Z","expires_at":"2026-11-13T16:58:11.265472Z","created_at":"2026-10-14T15:21:51.289264Z","updated_at":"2026-10-14T16:58:11.268263Z","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/7ef52fd3-3cc0-4c90-9f0a-f64a1b317d4e"},{"id":"1d949a93-d678-4755-b0f7-aca698eb1c9a","company_id":"b4787255-dacd-444b-8e44-bb9971ec1f36","title":"Senior Machine Learning Engineer","slug":"senior-machine-learning-engineer-d1dd4c03","description":"ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast.\n \n You'll help build the intelligence every ZoomInfo AI agent reasons over — what's true about companies and the people in them, how they relate, and what they're buying. You'll own outcomes end to end, from the data a model learns from to the product surface where its output lands, applying classical machine learning, statistics, or language models based on what the problem calls for. You'll take a problem in the data graph, entity resolution, or buying intent from design through production, and own it after launch.\n What You'll Do \n \n You will extract leadership, locations, and products from the websites of companies with almost no public footprint, and detect stale records, choosing which pages to read based on cost per document.\n You will estimate headcount and revenue for companies with sparse public information, using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty.\n You will determine whether two records describe the same company or person, measuring both false merges and false splits.\n You will infer buying intent from the meaning of what companies read, not keyword matches, across large volumes of multilingual, noisy text, feeding propensity scoring, lookalike retrieval, and contact recommendations.\n You will build research agents that cite their sources, along with the evaluation systems behind them: human labels, validated LLM judges, and regression gates.\n You will train small, task-specific models distilled from larger ones, measuring them against the larger model rather than against perfection, and own their quantization and serving.\n You will take a problem from design to production and own it after launch, including its evaluation and its cost, while helping other engineers improve their work through design and code review.\n \n What You Bring \n Must-Have: \n \n You have taken machine learning systems to production and owned them after launch, following the outcome into whichever layer it needs — depth matters more than years.\n You bring classical machine learning expertise beyond language models, including supervised learning and feature engineering on large, messy tabular data, along with applied statistics: experiment design, statistical inference, and calibrated scores under class imbalance.\n You have deployed language processing at scale — text classification, information extraction, and entity linking over large volumes of multilingual, noisy text.\n You have built LLM agents or multi-step systems in production, including tool and context design and failure analysis from traces, and you've evaluated systems with no single right answer using LLM judges validated against human labels.\n You are proficient in production Python and strong in SQL, with experience in distributed data processing, and you use AI coding tools daily, rigorously reviewing their output.\n \n Preferred: \n \n You have experience with ranking and retrieval, including embeddings, learned re-ranking, and metrics such as recall@k, MRR, and nDCG.\n You bring experience in propensity modeling, clustering, or entity resolution on messy, real-world data.\n You have trained and served open-weight models in PyTorch or an equivalent framework, with cost tracked per unit of work.\n You have defended LLM systems against adversarial inputs and prompt injection, or worked on web-scale information extraction, knowledge graphs, or user memory for agents.\n \n  \n  \n #LI-Remote\n #LI-VC1\n Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process. We want our employees and their families to thrive.\n In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits here .\n Below is the US base salary for this position. Additional compensation such as Bonus, Commission, Equity and other benefits may also apply.\n $128,100 — $201,300 USD \n About us:  \n ZoomInfo (NASDAQ: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller.\n ZoomInfo is committed to protecting your privacy when you apply for jobs with us. Please review our Job Applicant Privacy Notice for more details on how we handle your personal information.\n ZoomInfo may use ","salary_min":128100,"salary_max":201300,"location":"Bethesda, MD","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["nlp","pytorch","agents","llm","machine-learning","data-science"],"apply_url":"https://www.zoominfo.com/careers?gh_jid=8769474002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-21T18:38:41Z","expires_at":"2026-11-13T17:03:21.861603Z","created_at":"2026-10-14T15:25:25.428017Z","updated_at":"2026-10-14T17:03:21.864592Z","company_name":"ZoomInfo","company_slug":"zoominfo","company_logo_url":"https://www.google.com/s2/favicons?domain=zoominfo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1d949a93-d678-4755-b0f7-aca698eb1c9a"},{"id":"7b48d1ff-aa46-435a-aa83-a6a58bb9f9e5","company_id":"da5cfe83-4fb2-4ab3-9392-94069a77ae59","title":"Senior Software Engineer, Agentic Search","slug":"senior-software-engineer-ai-squad-team-7fbc5b61","description":"Build AI contracting at enterprise scale. Ship it fast.\n\nIronclad is building AI on one of the most consequential datasets in enterprise software: over 2 billion contracts across thousands of the world's largest organizations. Contracts run every dollar, deal, and business relationship on the planet, and the AI transformation of this space is still largely uncharted. Engineers here are building agentic solutions to problems that haven't been solved yet, in a category that's still being defined. The feedback loop is short, the data is rich, and the people closest to the work are the ones deciding what gets built next. That ability to deliver impact quickly is why the the companies at the forefront of AI choose Ironclad to manage their contracts.\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\nThis is a hybrid role. Office attendance is required at least twice a week on Tuesdays and Thursdays for collaboration and connection. There may be additional in-office days for team or company events.\n\n\n\n\nABOUT THE TEAM\n\nAt Intelligence Platform org, we own Ironclad's Agent Assistant, Conversational Search, and Content Understanding — the systems that help users and AI agents understand, find and act on the right contract information. These are the flagship AI capabilities of our product.\n\nThe team is a mix of ML and ML infrastructure engineers who build and operate these systems together.\n\n\n\n\nWHAT YOU'LL WORK ON\n\n - Agentic search systems: Evolve the architecture that combines LLM and retrieval system to produce optimal answer for complex or ambiguous questions.\n\n - Eval-driven development: Design and run the benchmarks and experiments that measure search quality, and use that feedback to improve the system.\n\n - Search quality: Contribute to the company's search quality bar.\n\n - Content understanding \u0026 ingestion: turn raw documents into processed data that can be consumed by retrieval systems, by building/using NLP/LLM models and pipelines\n\n\n\n\nWHO WE'RE LOOKING FOR\n\n - 4 years experience building production systems, with hands-on experience in search, information retrieval, content understanding or recommendation systems at meaningful scale.\n\n - Demonstrated expertise 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 workflow — offline benchmarks, regression detection, structured A/B comparison — as opposed to shipping and hoping.\n\n - Strong ownership and communication.\n\n - Care deeply about system scalability, reliability, and right design patterns.\n\n - Comfortable operating in a dynamic, fast-paced and outcome-driven environment.\n\n\n\nBase Salary Range: $180,000 - $200,000 offers company bonus\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 your tenure), competitive health and wellness benefits, and a commitment to career growth and development.\n\n\nUS Full-Time Employee Benefits at Ironclad:\n\n - 100% health coverage for employees (medical, dental, and vision), and 75% coverage for dependents with buy-up plan options available\n\n - Market-leading leave policies, including gender-neutral parental leave and compassionate leave\n\n - Family forming support through Maven for you and your partner\n\n - Paid time off - take the time you need, when you need it\n\n - Monthly stipends for wellbeing, hybrid work, and (if applicable) cell phone use\n\n - Mental health support through Modern Health, including therapy, coaching, and digital tools\n\n - Pre-tax commuter benefits (US Employees)\n\n - 401(k) plan with Fidelity with employer match (US Employee","salary_min":180000,"salary_max":200000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","search","nlp","agents"],"apply_url":"https://jobs.ashbyhq.com/ironcladhq/fa6f1cdc-4e73-4041-a8cc-aeb26a75e647/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-18T13:56:04.328Z","expires_at":"2026-11-13T16:58:49.164221Z","created_at":"2026-06-28T14:10:44.179083Z","updated_at":"2026-10-14T16:58:49.167319Z","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/7b48d1ff-aa46-435a-aa83-a6a58bb9f9e5"},{"id":"d8f1382a-dad3-4376-b0c9-0a68b5a32b33","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Staff Machine Learning Engineer(Platform - Identity)","slug":"staff-machine-learning-engineerplatform-identity-f49c217a","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n Staff Machine Learning Engineer, Identity Verification\n As a Staff Machine Learning Engineer on the Identity Verification team within the  Platform  group, you'll own the ML systems that determine whether a person, document, and capture session are legitimate. Every signup, account recovery, and high-risk action at Coinbase depends on these models. You'll lead the technical strategy for IDV ML end-to-end, from architecture through production enforcement, protecting the integrity of millions of accounts.\n What you'll do: \n \n Own the full IDV ML stack, including document authenticity models, 1:1 and 1:N face-match, liveness detection, presentation-attack detection, and deepfake/injection detection from feature pipeline through threshold tuning and production enforcement.\n Build identity-graph systems using GNNs that cluster accounts sharing biometric, device, and document signals to detect synthetic-identity rings and coordinated fraud at onboarding.\n Develop behavioral and device-intelligence models for capture-session anomaly detection, bot-vs-human classification, and device-fingerprint-based risk scoring at real-time latency.\n Drive vendor ML strategy by benchmarking external models against a Coinbase-owned evaluation set, designing dynamic routing logic across providers and geographies, and building the in-house evaluation layer that catches regressions before they reach users.\n Lead and mentor senior and mid-level engineers in the pod while partnering with ML Platform and Risk ML teams to align cross-company ML system design.\n \n Required Skills and Experience: \n \n 8+ years deploying production ML systems at scale, with proven technical leadership owning cross-team ML architecture from design through production.\n Domain experience in identity verification, biometrics, or account integrity with deep applied ML in at least two of: computer vision/biometrics, GNNs, sequence models, or NLP/LLMs.\n Expert-level Python with production experience in TensorFlow or PyTorch, including model training, evaluation, and serving infrastructure.\n Track record translating KYC/AML requirements and fraud trends into ML roadmaps and communicating trade-offs to Product, Compliance, Risk, and Security stakeholders.\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $218,025 — $256,500 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":218025,"salary_max":256500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["nlp","tensorflow","llm","computer-vision","pytorch","generative-ai","machine-learning"],"apply_url":"https://www.coinbase.com/careers/positions/8211486?gh_jid=8211486","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-17T19:38:43Z","expires_at":"2026-11-13T16:58:01.545659Z","created_at":"2026-10-14T15:21:41.472986Z","updated_at":"2026-10-14T16:58:01.548802Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d8f1382a-dad3-4376-b0c9-0a68b5a32b33"},{"id":"64c23faf-93ae-4f5f-a893-d8922f71e39f","company_id":"2721f049-2cf2-4e3e-82d0-8d8df89c8f90","title":"Senior Product Manager, Enterprise","slug":"senior-product-manager-enterprise-2ff6b764","description":"About Nebius: \n Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.\n Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.\n Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R\u0026D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R\u0026D.\n The role \n Tavily, part of Nebius, is the web access layer for AI agents. Over two million developers use us, and our customers include Fortune 500 companies running agents in production.\n You will own our enterprise product: the roadmap for what large customers need, and the control plane that makes it possible. These are the capabilities that decide whether a large customer can adopt us, trust us, and expand with us.\n Our product is an API, and our enterprise buyer is an engineering organization. The people you build for are platform teams, architects, and the developers inside those companies who are putting agents into production. You need to be comfortable making product decisions about API surfaces, developer workflows, and technical tradeoffs, not only about business requirements.\n To build this well, you have to be in the room. You will work alongside customer success, sales, and our forward-deployed engineers, who are in these accounts every week and already know where we fall short, and you will spend real time with customers alongside them. Delivery and implementation stay with forward-deployed engineering and go-to-market. Your job is to turn what you learn into product.\n The hard part is judgment. Knowing which request is one account's edge case, and which one is the thing every enterprise customer will ask for six months from now. Getting that right is the difference between a platform and a pile of custom work.\n In your first year, we expect you to own a clear enterprise roadmap, ship the controls that block deals today, and become the person the go-to-market team comes to before a deal gets stuck.\n This is a hands-on senior IC role with real ownership, reporting to the Director of Product. The product team is small, so you will work directly with the engineers building your roadmap and with the go-to-market teams selling it.\n Your responsibilities will include \n \n Own the enterprise roadmap: what we build for large customers, in what order, and why.\n Own the platform behind it: organizations and identity, keys and quotas, spend controls, usage observability and audit, policy enforcement, and data residency.\n Make product decisions on our API surface for enterprise use, so that the developers inside those accounts can build on us without friction.\n Work with customer success, sales, and forward-deployed engineering to understand what enterprise customers need, and spend time in accounts alongside them to see it first hand.\n Tell the difference between a single-account request and a pattern worth building for, and be able to defend the call either way.\n Hand off what belongs to another product area, with the evidence that makes it actionable.\n Give sales and marketing the positioning, materials, and product understanding they need to sell a technical product well.\n Represent enterprise customers in roadmap decisions with evidence rather than anecdote.\n \n We expect you to have \n \n 6+ years of product management experience, with a meaningful part of it spent on enterprise products in B2B, developer platform, or API businesses.\n Experience building developer-facing or API products, with real understanding of what makes an API good to build against.\n Experience building platform capabilities that enterprises depend on, such as identity, permissions, quotas, usage controls, audit, or compliance.\n A track record of working with large enterprise accounts, including recognized logos, and turning what you learned into shipped product.\n Credibility with technical buyers: platform teams, architects, security, and procurement.\n Strong understanding of LLMs, AI agents, and how search and retrieval fit into agentic workflows. Hands-on technical background is a strong plus.\n The ability to turn many messy customer conversations into one clear, prioritized product argument.\n Proven ability to drive alignment without formal authority, including with product owners who do not report to you.\n \n It will be a bonus if you have \n \n Background as a forward-deployed engineer, solutions engineer, or solutions architect before moving into product.\n Experience in search, information retrieval, or NLP.\n Experience in API-first businesses running both self-serve and enterprise m","salary_min":179500,"salary_max":224300,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["search","nlp","healthcare","agents","llm","cloud","infrastructure"],"apply_url":"https://careers.nebius.com/?gh_jid=4973737101","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-16T23:40:36Z","expires_at":"2026-11-13T17:00:03.526237Z","created_at":"2026-10-14T15:23:35.254095Z","updated_at":"2026-10-14T17:00:03.529876Z","company_name":"Nebius","company_slug":"nebius","company_logo_url":"https://www.google.com/s2/favicons?domain=nebius.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/64c23faf-93ae-4f5f-a893-d8922f71e39f"},{"id":"8525ccc4-39a3-4e02-844b-f5c799b58d92","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Staff Machine Learning Engineer, AI Security","slug":"staff-machine-learning-engineer-ai-security-3a1851c1","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 The AI Security team within Reddit’s Security Platform Engineering organization builds security into Reddit’s products, engineering systems, AI platforms, and operational infrastructure so the secure path is the easiest path for both people and agents. A core part of this work is developing practical, high-quality machine learning systems that detect and prevent risks such as prompt injection, jailbreaks, sensitive data exposure, and unsafe or unauthorized AI behavior. Building on Reddit’s centralized LLM Guardrails Platform, which provides a shared security and safety boundary across major products, we are expanding ML-powered protections as Reddit’s AI systems and threat landscape evolve.\n We are looking for a founding Staff Machine Learning Engineer to lead the development, training, and optimization of models for AI security at Reddit. This is a strategic and hands-on individual contributor role, combining deep ownership of model architecture, training data, and experimentation with technical leadership across teams. You will help Reddit deliver stronger AI protections while preserving a high-quality product experience.\n How You’ll Have Impact \n \n Select, adapt, fine-tune, evaluate, and deploy pretrained models and lightweight classifiers for Reddit-specific security problems.\n Build reproducible training and evaluation pipelines on Reddit’s ML platform, partnering with platform engineers to improve inference performance, resource efficiency, and operational reliability.\n Set the technical vision and multi-quarter modeling roadmap, partnering with cross-functional teams to gather requirements, define model architectures, and iterate on model development.\n Conduct model evaluations and performance analysis to improve accuracy and adversarial robustness, and define launch criteria that balance false positives, latency, throughput, reliability, and cost.\n Own training-data quality and the production model lifecycle, using monitoring, incident findings, and red-team feedback to guide dataset improvements, retraining, and safe rollout or rollback.\n Establish best practices for responsible ML development and deployment, including reproducible experiments, testing, model and data lineage, and privacy-aware data use.\n Stay current with research in NLP, large language models, and relevant multimodal techniques, translating promising advances into measurable model improvements.\n Mentor engineers and lead technical discussions and reviews, shaping the team’s long-term ML capabilities and AI security direction.\n \n Who You Might Be \n \n 8+ years of experience developing machine learning models, with substantial hands-on model training experience, demonstrated production impact, and a record of leading complex initiatives across teams.\n Strong background in Python programming, software engineering, and deep learning frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.\n Deep understanding of neural network architectures and optimization, with proficiency in data preprocessing, tokenization, embeddings, language modeling, and model calibration.\n Expertise in scalable data pipelines and distributed training frameworks such as Ray Train or PyTorch Distributed, with a strong understanding of hardware and system tradeoffs.\n Demonstrated rigor in experimental design and model evaluation, including representative holdouts, ablation studies, adversarial tests, and error analysis to diagnose training issues, bias, and generalization gaps.\n Excellent written and verbal communication, with the ability to explain model behavior, security risk, uncertainty, and tradeoffs to technical and non-technical partners.\n \n Preferred Qualifications \n \n Experience applying ML to security, trust and safety, fraud, privacy, or related adversarial domains.\n Experience with adversarial training, model distillation, active learning, or synthetic-data generation to improve model quality, robustness, and training efficiency.\n \n Benefits: \n \n Comprehensive Healthcare Benefits and Income Replacement Programs\n 401k with Employer Match\n Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support\n Family Planning Support\n Gender-Affirming Care\n Mental Health \u0026 Coaching Benefits\n Flexible Vacation \u0026 Paid Volunteer Time Off\n Generous Paid Parental Leave \n \n #LI-Remote\n Pay Transparency: \n This job posting may span more than one career level.\n In addition to base salary, this job is eligible to receive equit","salary_min":230000,"salary_max":322000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["tensorflow","llm","healthcare","pytorch","deep-learning","distributed-systems","nlp","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8203478","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-15T06:07:12Z","expires_at":"2026-11-13T16:57:52.338467Z","created_at":"2026-10-14T15:21:32.503725Z","updated_at":"2026-10-14T16:57:52.34155Z","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/8525ccc4-39a3-4e02-844b-f5c799b58d92"},{"id":"9b730dc7-f409-4bcd-9f2a-dd0979c6cdab","company_id":"280644c0-35ed-4161-9de3-24c4751b2c00","title":"Senior AI Software Engineer, Risk - Insurance Claims Management","slug":"senior-ai-software-engineer-risk-insurance-claims-management-e42d796a","description":"At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.\n The Risk Tech engineering organization is committed to tangibly reducing accident frequency, saving lives, and managing costs to enhance the safety and affordability of rides.\n Claim Management is a core financial function for Lyft. Each claim touches complex workflows, multiple stakeholders, sensitive data, financial reserves, regulatory processes, and significant financial liabilities.\n This role offers the opportunity to define a leading claims management system for the industry. Our vision is to establish a single, Unified Risk Platform where comprehensive claims workflows across all business lines are efficiently administered, communications are consolidated, and data is structured to facilitate data-driven insights and decisions.\n This enables cost-efficient claims operations, mitigates risks and expenses as Lyft scales, and ensures people receive assistance proactively and accurately.\n We are seeking a Senior Software Engineer to contribute to the technical direction, drive architectural decisions, and lead the development of a highly reliable, scalable, and intelligent Risk Management Information System that powers our insurance platform. You will collaborate with passionate colleagues from Engineering, Data Science, Product and Claim Operations to deliver end-to-end solutions.\n  Responsibilities: \n \n Define and drive the long-term technical roadmap for claims management systems, aligning priorities with Product, Claim Operations, Data Science, and other stakeholders.\n Provide architectural leadership, make informed design tradeoffs, and guide strategic decisions across multiple engineering teams.\n Understand claim handling workflows, identify bottlenecks and multiply their productivity by driving platform innovations and resolving pain points with AI automation solutions\n Deliver scalable, reliable, high quality and well-tested solutions and code.\n Collaborate closely with Lyft internal teams and external insurance partners to ensure technical alignment and scalable integrations.\n Lead code reviews, design reviews, production on-call support and incident triaging process.\n Invest in the engineering community through knowledge sharing via brown bags, tech talks, and suggesting improvements to team processes and engineering practices.\n \n Experience: \n \n B.S., M.S. in Computer Science or related technical field or relevant work experience.\n 6+ years of professional experience building scalable distributed systems with high availability, observability and reliability requirements.\n Proven ability to build end-to-end products and platforms, collaborating effectively with various stakeholders e.g. Backend, Frontend, Data Engineering, Data Science, Claim Operations, and Product teams.\n Strong ability to reason about tradeoffs in system design, architecture, domain modeling, and operational cost.\n Experience developing AI features using multimodal LLMs, RAG pipelines, agentic workflows, and other relevant AI frameworks.\n Experience driving AI adoption or AI automation tools to enhance development efficiency\n Experience improving performance with robust evals,agent tracing tools, fine-tuning LLMs, optimizing RAG pipelines and implementing feedback loops.\n Proficiency in Python. Knowledge of React/Next.js and data analysis is a plus.\n Experience with data processing frameworks and tools like Spark, Kafka, Airflow and cloud provisioning environments etc.\n Strong oral and written interpersonal skills.\n Preferred: \n \n Prior experience in insurance, claims management, workflow orchestration or external vendors is a strong plus.\n Has knowledge about AI safety and alignment considerations.\n Background in machine learning, NLP, or related fields.\n Experience with A/B testing and experimentation frameworks\n \n \n Benefits: \n \n Great medical, dental, and vision insurance options with additional programs available when enrolled\n Mental health benefits\n Family building benefits\n Child care and pet benefits\n 401(k) plan to help save for your future\n In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off\n 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible\n Subsidized commuter benefits\n Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program\n \n Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent","salary_min":136160,"salary_max":170200,"location":"Seattle, WA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["rag","distributed-systems","agents","llm","fine-tuning","alignment","nlp"],"apply_url":"https://app.careerpuck.com/job-board/lyft/job/8806969002?gh_jid=8806969002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-14T21:09:50Z","expires_at":"2026-11-13T16:57:53.456022Z","created_at":"2026-10-14T15:21:33.513659Z","updated_at":"2026-10-14T16:57:53.459975Z","company_name":"Lyft","company_slug":"lyft","company_logo_url":"https://www.google.com/s2/favicons?domain=www.lyft.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9b730dc7-f409-4bcd-9f2a-dd0979c6cdab"}],"page":1,"per_page":20,"total":276,"total_is_exact":true,"total_pages":14}