{"has_next":true,"jobs":[{"id":"48720738-0f4b-483d-9739-14039ae457d0","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Engineer, Performance RL","slug":"research-engineer-performance-rl-2f0da25a","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the RL Teams \n Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.6 and Opus 4.6. Our work spans several key areas:\n \n \n Developing systems that enable models to use computers effectively\n \n Advancing code generation through reinforcement learning\n \n Pioneering fundamental RL research for large language models\n \n Building scalable RL infrastructure and training methodologies\n \n Enhancing model reasoning capabilities\n \n We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.\n About the Role \n We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to safely write correct, fast code for accelerators.\n You'll need to know accelerator performance well to turn it into tasks and signals models can learn from. Specifically, you will:\n \n \n Invent, design and implement RL environments and evaluations.\n \n Conduct experiments and shape our research roadmap.\n \n Deliver your work into training runs.\n \n Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic.\n \n You may be a good fit if you:\n \n \n Have expertise with accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch).\n \n Have worked across the stack – kernels, model code, distributed systems.\n \n Know how to balance research exploration with engineering implementation.\n \n Are passionate about AI's potential and committed to developing safe and beneficial systems.\n \n Strong candidates may also have:\n \n \n Experience with reinforcement learning.\n \n Experience porting ML workloads between different types of accelerators.\n \n Familiarity with LLM training methodologies.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $350,000 — $850,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a ","salary_min":350000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"principal","tags":["reinforcement-learning","gpu","code-generation","distributed-systems","search","jax","fine-tuning","llm"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5160330008","is_featured":true,"is_sticky":true,"status":"active","published_at":"2026-03-23T16:27:59Z","expires_at":"2026-06-29T14:00:21.52187Z","created_at":"2026-04-13T09:36:00.086246Z","updated_at":"2026-05-30T14:00:21.633054Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/48720738-0f4b-483d-9739-14039ae457d0"},{"id":"f8c6c621-b459-40f6-b41d-0baa191734ff","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Lead, Training Insights","slug":"research-lead-training-insights-6091f430","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n As a Research Lead on the Training Insights team, you'll develop the strategy for, and lead execution on, how we measure and characterize model capabilities across training and deployment. This is a hands-on leadership role: you'll drive original research into new evaluation methodologies while leading a small team of researchers and research engineers doing the same.\n Your work will span the full lifecycle of model development. You'll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop — both during production RL training and after. You'll also take a cross-organizational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.\n This role carries significant visibility and impact. You'll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.  \n Responsibilities:  \n \n Build new novel and long-horizon evaluations\n Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training\n Lead strategic evaluation coverage across the company\n Shape the evaluation narrative for model releases\n Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research\n Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules\n Build and maintain relationships across Anthropic's research organization to ensure evaluation insights inform training and deployment decisions\n Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices\n \n You may be a good fit if you:  \n \n Have significant experience designing and running evaluations for large language models or similar complex ML systems\n Have led technical projects or teams, either formally or through sustained ownership of critical research directions\n Are equally comfortable designing experiments and writing code—you can move between research and implementation fluidly\n Think strategically about what to measure and why, not just how to measure it\n Can synthesize information across multiple teams and workstreams to form a coherent picture of model capabilities\n Communicate complex technical findings clearly to both technical and non-technical audiences\n Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings\n Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed\n \n Strong candidates may also have:  \n \n Experience building evaluations for long-horizon or agentic tasks\n Deep familiarity with Reinforcement Learning training dynamics and how model behavior changes during training\n Published research in machine learning evaluation, benchmarking, or related areas\n Experience with safety evaluation frameworks and red teaming methodologies\n Background in psychometrics, experimental psychology, or other measurement-focused disciplines\n A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment\n Experience managing or mentoring researchers and engineers\n \n Representative projects:  \n \n Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions\n Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge\n Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritizing new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product\n Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterize model capabilities and limitations\n Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks\n Leading a team","salary_min":850000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","pre-training","agents","alignment","search","llm","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5139654008","is_featured":true,"is_sticky":false,"status":"active","published_at":"2026-03-06T17:15:29Z","expires_at":"2026-06-29T14:00:22.960238Z","created_at":"2026-04-13T09:36:01.625992Z","updated_at":"2026-05-30T14:00:23.075652Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f8c6c621-b459-40f6-b41d-0baa191734ff"},{"id":"b2263952-2d61-4a59-acd2-4d8506c9b16e","company_id":"cf6855a4-6591-475f-be10-f3f36cf31758","title":"Senior Software Engineer, Search Relevance","slug":"senior-software-engineer-search-relevance-8f221ba2","description":"WHAT IS BOX?  \n Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia.\n By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift.\n WHY BOX NEEDS YOU \n The Search Relevance team at Box powers discovery across billions of files, enabling customers to find the right content quickly, securely, and intelligently. As we expand into a new era of AI-powered content understanding, we’re investing in the foundation that makes great search possible: reliable systems, strong signals, and models that learn from real-world usage.\n This is a rare opportunity to work at the intersection of information retrieval science, applied machine learning, and large-scale distributed systems. You’ll be building the infrastructure that powers intelligent content discovery for Fortune 500 companies—where milliseconds matter, relevance is measurable, and your experiments directly impact how millions of users work.\n We’re looking for a Senior Software Engineer to elevate search quality end-to-end—signals, ranking, retrieval, and evaluation—while building scalable, low-latency services that serve queries in real time. You’ll partner with Product, Data, and Infra teams to productionize cutting-edge models and experimentation frameworks, and help define the future of Box’s content intelligence, including hybrid and semantic search and our next-generation content agent.\n WHAT YOU'LL DO  \n \n Build and improve ranking, retrieval, and recommendation systems; identify the right signals and metrics to drive quality improvements that users can feel.\n Apply cutting-edge techniques (embeddings, LLM-enabled retrieval, hybrid search) to productionize experimentation and evaluation pipelines that scale to trillions of documents.\n Define and execute offline/online evaluation, A/B testing, and relevance tuning (NDCG, MRR, precision@k) to continuously improve search outcomes.\n Develop infrastructure for low-latency, high-availability query serving and near real-time indexing across distributed systems.\n Tackle distributed systems challenges including data sharding, intelligent routing, replication, and performance optimization.\n From ETL pipelines and feature engineering to model serving and result ranking—understand how data flows through the system and optimize at every stage.\n Lead design and implementation of new platform components from the ground up; establish patterns, raise the bar on code quality, and champion best practices.\n Share your expertise, contribute to technical direction, conduct thoughtful code reviews, and help shape our engineering culture.\n Participate in our on-call rotation, available at all times while on-call to help respond to and triage any issues that arise.\n \n WHO YOU ARE  \n \n 5+ years of industry experience building and operating backend or distributed systems at scale.\n Strong proficiency in an object-oriented language (e.g., Java, Scala, C++, or Python); Python experience strongly preferred.\n Hands-on experience building ranking, recommendation, NLP, or applied AI platforms in production. You understand the ML lifecycle from training to serving.\n Comfortable with data pipelines, message queues, and/or streaming systems (e.g., Kafka, Pub/Sub) and near real-time data processing.\n Experienced deploying and operating microservices in cloud environments; solid grasp of reliability, observability, and performance best practices.\n BS in Computer Science or related field, or equivalent practical experience.\n AI-first mindset—pragmatic about using the right models, signals, and evaluation methods to improve outcomes quickly and measurably.\n \n PREFERRED \n \n Experience with Elasticsearch, Solr, Lucene, or building custom search systems; deep understanding of inverted indexes, scoring functions, and query optimization.\n Knowledge of ML relevance tuning, learning-to-rank, retrieval evaluation metrics, offline/online testing, and A","salary_min":198500,"salary_max":248000,"location":"Redwood City, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["search","tensorflow","distributed-systems","pytorch","llm","nlp","fine-tuning","mlops"],"apply_url":"https://job-boards.greenhouse.io/boxinc/jobs/7926452","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T19:12:52Z","expires_at":"2026-06-29T14:19:20.83221Z","created_at":"2026-05-29T15:11:42.002134Z","updated_at":"2026-05-30T14:19:20.940887Z","company_name":"Box","company_slug":"box","company_logo_url":"https://www.google.com/s2/favicons?domain=box.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b2263952-2d61-4a59-acd2-4d8506c9b16e"},{"id":"0ed6f2c3-8d05-4541-a58a-3bc3eb48b078","company_id":"1a3abe34-d1c1-45b9-9259-3e2e007a961c","title":"Staff Research Scientist","slug":"staff-research-scientist-6193df9d","description":"About Voyage AI Team at MongoDB\n Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions.\n Position Overview\n We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks.\n This role can be based out of our Palo Alto office, or remotely in the United States.\n Responsibilities\n \n Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers\n Innovate in next-generation information retrieval and LLM agent paradigm\n Collaborate closely with other research scientists and research engineers as well as peers across the organization\n \n Qualifications\n \n PhD degree in Computer Science or related field\n A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues\n Strong background in machine learning, deep learning, and natural language processing\n Experience building complex neural networks for language and visual understanding\n Capable of conducting rigorous empirical studies to validate theoretical results\n Excellent leadership, problem-solving, and communication skills\n \n What We Offer\n \n Opportunity to work on real-world problems at the cutting edge of AI research\n Opportunity to utilize research vision to innovate the entire company and make real-world impact\n Exposure to the full lifecycle of AI model development, from research to production\n Our compensation (base + equity) for this position is competitive with frontier AI labs\n \n About MongoDB \n MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.\n With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.\n Our compass at MongoDB is our  Leadership Commitment,  guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.\n To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone.  From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys.  Learn more about what it’s like to work at MongoDB , and help us make an impact on the world!\n MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.\n MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions 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.\n Req ID: 2273454547\n MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to ","salary_min":151000,"salary_max":297000,"location":"Palo Alto, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["nlp","computer-vision","search","llm","embeddings","deep-learning","research"],"apply_url":"https://www.mongodb.com/careers/job/?gh_jid=7956670","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T17:21:23Z","expires_at":"2026-06-29T14:08:48.853182Z","created_at":"2026-05-29T14:32:41.960202Z","updated_at":"2026-05-30T14:08:48.964003Z","company_name":"MongoDB","company_slug":"mongodb","company_logo_url":"https://www.google.com/s2/favicons?domain=www.mongodb.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0ed6f2c3-8d05-4541-a58a-3bc3eb48b078"},{"id":"0ffaba88-636c-40f6-b308-69d1b07a2471","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Platform AI Engineer","slug":"senior-platform-ai-engineer-4ad89166","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata's AI Platform team builds the production infrastructure that powers AI features across our compliance platform — from MCP servers that make Drata's data available to AI agents, to LLM workflow orchestration that automates SOC 2, TPRM, and policy analysis. You'll own the systems that sit between our AI models and our customers: tool definitions that agents actually understand, deployment pipelines that handle model upgrades without breaking output quality, and orchestration layers that manage multi-step agent workflows with persistent state.\n\nThis is not a traditional infrastructure role. You'll debug prompt templates alongside Terraform modules. You'll design API schemas optimized for LLM token budgets, not just HTTP throughput. When a model upgrade changes behavior across 15 workflows, you'll assess quality impact — not just confirm the containers are healthy.\n\nYou'll work closely with our agent developers, product engineers, and an embedded SRE partner, sitting at the intersection of AI development and production reliability.\n\nOur north star is simple: minimize the time it takes to launch a new agent in production. You're someone who asks \"are we solving the right problem?\" before writing the first line of code, who builds systems that make five other engineers faster, not just yourself, and who's equally proud of what they chose not to build.\n\nWhat you'll do:\n\n\nMCP SERVER DEVELOPMENT \u0026 AI-OPTIMIZED API DESIGN\n\n - Design and build MCP (Model Context Protocol) servers that expose Drata's platform to AI agents. This means making architectural decisions about tool granularity, naming conventions for agent disambiguation, response compression for LLM context windows, and workspace isolation for multi-tenant access. You'll own the protocol layer that determines whether agents can reliably find and use the right tools — writing semantic parameter descriptions, contextual hints, and tool schemas that optimize for model comprehension, not just developer ergonomics.\n\n\nAGENT ORCHESTRATION \u0026 WORKFLOW INFRASTRUCTURE\n\n - Build and operate the infrastructure for deploying multi-step agent workflows — state management across complex reasoning chains, tool routing and execution runtimes, and long-running agentic processes that persist over time. Own the orchestration layer that coordinates agent planning, tool calls, and human-in-the-loop patterns. Design systems that handle agent failure modes gracefully: retries on ambiguous tool ","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","search","healthcare","llm","cloud","rag","agents","api-design"],"apply_url":"https://jobs.ashbyhq.com/drata/f0ab62fb-c0a8-4bf2-bfd6-9d9d2e68fb91/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T23:02:26.469Z","expires_at":"2026-06-29T14:13:56.372048Z","created_at":"2026-05-27T14:14:32.001255Z","updated_at":"2026-05-30T14:13:56.493566Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0ffaba88-636c-40f6-b308-69d1b07a2471"},{"id":"84366e11-6b70-4a34-a8c9-d03cd29bd00e","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Applied Research Engineer","slug":"senior-applied-research-engineer-a868acf4","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking a Senior Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 5+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 2+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research wo","salary_min":166900,"salary_max":225900,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["nlp","generative-ai","rag","embeddings","search","llm","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/fab401cd-087e-4b69-8a62-f0dbae4906c9/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T22:59:45.262Z","expires_at":"2026-06-29T14:13:57.168877Z","created_at":"2026-05-27T14:14:33.203504Z","updated_at":"2026-05-30T14:13:57.34909Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/84366e11-6b70-4a34-a8c9-d03cd29bd00e"},{"id":"96ba0be2-0b27-42c5-bc86-c4ffbb0b4359","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Applied Research Engineer","slug":"applied-research-engineer-8d39811c","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking an Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 3+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 1+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research workflow","salary_min":145200,"salary_max":196400,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["rag","generative-ai","embeddings","search","llm","nlp","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/51a418d1-c371-4f9f-b248-2c3b542bec42/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:47.784Z","expires_at":"2026-06-29T14:13:57.088082Z","created_at":"2026-05-27T14:14:33.116975Z","updated_at":"2026-05-30T14:13:57.199158Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/96ba0be2-0b27-42c5-bc86-c4ffbb0b4359"},{"id":"cb6155b3-db5f-4d05-a1db-f321ee0718be","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Applied Research Engineer 2","slug":"senior-applied-research-engineer-2-fcdd01a9","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking a Senior Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 6+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 2+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research wo","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["rag","llm","generative-ai","healthcare","nlp","agents","embeddings","search"],"apply_url":"https://jobs.ashbyhq.com/drata/e66701e1-f52f-471b-9bcc-400e874c651c/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:39.187Z","expires_at":"2026-06-29T14:13:56.779385Z","created_at":"2026-05-27T14:14:32.761406Z","updated_at":"2026-05-30T14:13:56.891705Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cb6155b3-db5f-4d05-a1db-f321ee0718be"},{"id":"4ed2ca6e-f534-411e-b47e-bc955d32008f","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Staff Applied Research Engineer","slug":"staff-applied-research-engineer-b2f192cc","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata, at the vanguard of compliance software innovation and renowned for its commitment to trust and security across the internet, is on an ambitious path to redefine how AI and General AI technologies bolster compliance automation.\n\nDrata is seeking an Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous research, experimentation, and evaluation. In this role, you will optimize retrieval strategies, build evaluation frameworks, and establish the scientific foundation that enables our AI features to deliver accurate, trustworthy results.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll work closely with AI Engineers handing off validated approaches for them to productionize while owning the quality metrics and evaluation systems that ensure our AI delivers on its promises.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and regulatory summarization all depend on retrieving the right information from large document sets. Your work will directly impact how well our AI understands and navigates compliance artifacts.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, structured retrieval, tool use, and multi-step workflows\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and weak supervision\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 10+ years of experience in applied research, data science, or ML ","salary_min":220800,"salary_max":298800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["search","embeddings","rag","healthcare","agents","generative-ai","nlp","llm"],"apply_url":"https://jobs.ashbyhq.com/drata/5fe5bc38-678d-468f-a762-a2144e88e45e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:23:45.786Z","expires_at":"2026-06-29T14:13:56.857373Z","created_at":"2026-05-27T14:14:32.846263Z","updated_at":"2026-05-30T14:13:56.969043Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4ed2ca6e-f534-411e-b47e-bc955d32008f"},{"id":"3a790011-3259-4ddc-b03a-1e3227951d9b","company_id":"c587b06c-b6f0-4d1d-b694-6fb6abc2a6bb","title":"Forward Deployed Engineer","slug":"forward-deployed-engineer-988ebd0a","description":"Who We Are \n Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.\n Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.\n We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.\n  \n What We Are Looking For \n We are seeking an experienced  Forward Deployed Engineer  to partner directly with customers to architect, build, and deploy production AI systems and workflows on Lightning AI’s platform. In this role, you will own the customer journey from early exploration through production deployment, translating ambiguous business goals into reliable, observable systems with clear quality, latency, scalability, and cost outcomes.\n This role sits at the intersection of software engineering, research engineering, AI infrastructure, product thinking, and customer engagement. You’ll work closely with customer engineering teams as well as Lightning’s internal product and engineering organizations to deliver production-ready AI systems that help customers realize value quickly and scale with confidence.\n This is a hands-on engineering role that combines software development, AI infrastructure, technical customer engagement, and product thinking. Successful candidates will be  highly technical, customer-oriented builders who thrive in fast-moving environments and enjoy solving ambiguous, real-world AI systems problems.\n This role is based in one of our hubs (New York City, San Francisco, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. \n What You'll Do \n \n Partner directly with customers to design, implement, and deploy end-to-end AI systems and workflows on Lightning’s platform\n Translate vague customer objectives into clear technical specifications, proof-of-concepts, and scalable production implementations\n Own customer technical engagements end-to-end, from early discovery and architecture through deployment, monitoring, and expansion\n Develop and maintain production-grade software systems and services using modern programming languages, with a strong preference for Python\n Build reliable, observable systems with strong attention to latency, throughput, quality, scalability, and cost efficiency in production environments\n Debug and optimize AI systems across inference infrastructure, model behavior, APIs, and distributed workloads to improve performance and reliability\n Work closely with customer engineering teams throughout the full lifecycle of AI deployments, including technical discovery, implementation, deployment, and scaling\n Collaborate cross-functionally with Lightning’s product and engineering teams to improve platform capabilities, influence roadmap priorities, and identify opportunities for reusable product improvements\n Navigate ambiguity with sound technical judgment, making thoughtful tradeoffs and selecting the right tools and approaches without introducing unnecessary complexity\n Demonstrate strong ownership and accountability in execution, with a commitment to delivering high-quality outcomes for both customers and internal teams\n \n What You’ll Need \n Required Qualifications \n \n Strong software engineering experience building and maintaining production systems in one or more general-purpose programming languages, with Python strongly preferred\n Experience working directly with customers in highly technical environments, such as Forward Deployed Engineering, Solutions Engineering, Applied AI Engineering, Technical Product Engineering, or related roles\n Familiarity with AI/ML pipelines and the lifecycle of model development, evaluation, deployment, and monitoring\n Experience deploying and operating production AI/ML systems in cloud or distributed environments\n Familiarity with modern AI infrastructure and tooling such as Docker, Kubernetes, APIs, model serving systems, or distributed inference workloads\n Strong communication and collaboration skills, especially when working through complex technical topics with customers, engineers, and cross-functional stakeholders\n Ability to translate business needs into technical solutions and drive projects from initial concept through production delivery\n Ability to execute effectively in ambiguous, fast-moving, high-growth environments\n Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field\n \n Nice-to-Haves \n \n Experience building, deploying, or optimizing large-scale AI/ML","salary_min":120000,"salary_max":250000,"location":"London, UK","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["distributed-systems","fine-tuning","pytorch","embeddings","search","llm","mlops"],"apply_url":"https://job-boards.greenhouse.io/lightningai/jobs/7742081003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T17:15:55Z","expires_at":"2026-06-29T14:03:02.726355Z","created_at":"2026-05-27T14:03:14.78242Z","updated_at":"2026-05-30T14:03:02.834329Z","company_name":"Lightning AI","company_slug":"lightning-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=lightning.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3a790011-3259-4ddc-b03a-1e3227951d9b"},{"id":"8b4e6266-a45b-4d9c-ba83-a52d6e425432","company_id":"d8e15a46-b80d-4228-8e7b-34f00357f377","title":"Principal Product Manager, AI agents - Search","slug":"principal-product-manager-ai-agents-search-92de566d","description":"Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.\n What is The Role \n Elastic, the Search AI Company, is looking for a Principal Product Manager to guide the vision, strategy, and execution for the Elastic Agent Builder. As organizations shift from traditional data retrieval to autonomous, agentic workflows, the Agent Builder serves as the critical context layer that enables users to make Agents faster, lower cost, and more accurate. In this high-impact role, you will be responsible for defining how enterprises build, manage, and scale context for AI agents. You will work at the cutting edge of the AI ecosystem, working with senior leadership and partnering with hyperscalers and evangelizing our solutions to a global community of AI developers.\n What You Will Be Doing \n \n Work directly with enterprise customers, sales teams, and solution architects to understand requirements, negotiate priorities, clarify product needs \n Build, socialize and align a roadmap for core context engineering capabilities built on top of Elastic powered retrieval and relevance for AI Agents \n Deeply understand the AI Agent market, major players, trends and how it may impact our strategy \n Work directly data science and engineering to build out the strategy for benchmarking and evaluations of agent capabilities \n Work with design to build user experiences that address gaps in how agents show and refine context as they work\n Be the product expert and evangelize capabilities for Agent Builder through content like blog posts and open source projects  \n Work with a broad ecosystem of AI partners including cloud service providers (Google, Amazon, Microsoft) and community developers \n \n What You Bring \n \n Extensive Experience: 10+ years of experience in product management or solution delivery for technical, cloud infrastructure, or platform products. A consistent record of leading sophisticated, data-intensive products from inception through launch and iterative growth.   \n AI and ML Fluency: Deep technical understanding of the AI/ML landscape, including LLMs, RAG architectures, vector databases, and context engineering. You are comfortable working closely with engineers and data scientists to solve intricate technical challenges.   \n Bias to action: You are able to move fast and quickly learn from experiments and tests. You utilize AI tools to help accelerate your processes and bring clarity to your decisions. \n Leadership and Influence: Demonstrated ability to lead across a matrixed organization, align multiple stakeholders toward a common vision, and drive execution in a fast-paced, remote-first environment.   \n Communication Excellence: Outstanding spoken and written communication skills. You can distill complex engineering details into compelling narratives for both technical and non-technical audiences, including executive leadership.   \n Customer Obsession: A passion for industry trends and a commitment to solving real-world customer problems. You are an advocate for the developer persona and are dedicated to building products that empower users to innovate.\n Compensation for this role is in the form of base salary.  This role does not have a variable compensation component.  The typical starting salary range for new hires in this role is listed below. \n These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting.  We may ultimately pay more or less than the posted range, and the ranges may be modified in the future.  \n An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.\n Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program.  Our total rewards package also includes a company-matched Registered Retirement Savings Plan (RRSP) with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being.\n The typical starting salary range for this role is:\n $154,000 — $243,6","salary_min":154000,"salary_max":243600,"location":"Canada","workplace":"remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","search","cloud","agents","rag","llm"],"apply_url":"https://jobs.elastic.co/jobs?gh_jid=7950453\u0026gh_jid=7950453","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T15:40:25Z","expires_at":"2026-06-29T14:08:43.627581Z","created_at":"2026-05-27T14:08:57.673316Z","updated_at":"2026-05-30T14:08:43.73747Z","company_name":"Elastic","company_slug":"elastic","company_logo_url":"https://www.google.com/s2/favicons?domain=www.elastic.co\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8b4e6266-a45b-4d9c-ba83-a52d6e425432"},{"id":"b29b4009-8754-46c6-93f3-879cf9cf064a","company_id":"d8e15a46-b80d-4228-8e7b-34f00357f377","title":"Principal Product Manager, AI agents - Search","slug":"principal-product-manager-ai-agents-search-6e2af9a0","description":"Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.\n What is The Role \n Elastic, the Search AI Company, is looking for a Principal Product Manager to guide the vision, strategy, and execution for the Elastic Agent Builder. As organizations shift from traditional data retrieval to autonomous, agentic workflows, the Agent Builder serves as the critical context layer that enables users to make Agents faster, lower cost, and more accurate. In this high-impact role, you will be responsible for defining how enterprises build, manage, and scale context for AI agents. You will work at the cutting edge of the AI ecosystem, working with senior leadership and partnering with hyperscalers and evangelizing our solutions to a global community of AI developers.\n What You Will Be Doing \n \n Work directly with enterprise customers, sales teams, and solution architects to understand requirements, negotiate priorities, clarify product needs \n Build, socialize and align a roadmap for core context engineering capabilities built on top of Elastic powered retrieval and relevance for AI Agents \n Deeply understand the AI Agent market, major players, trends and how it may impact our strategy \n Work directly data science and engineering to build out the strategy for benchmarking and evaluations of agent capabilities \n Work with design to build user experiences that address gaps in how agents show and refine context as they work\n Be the product expert and evangelize capabilities for Agent Builder through content like blog posts and open source projects  \n Work with a broad ecosystem of AI partners including cloud service providers (Google, Amazon, Microsoft) and community developers \n \n What You Bring \n \n Extensive Experience: 10+ years of experience in product management or solution delivery for technical, cloud infrastructure, or platform products. A consistent record of leading sophisticated, data-intensive products from inception through launch and iterative growth.   \n AI and ML Fluency: Deep technical understanding of the AI/ML landscape, including LLMs, RAG architectures, vector databases, and context engineering. You are comfortable working closely with engineers and data scientists to solve intricate technical challenges.   \n Bias to action: You are able to move fast and quickly learn from experiments and tests. You utilize AI tools to help accelerate your processes and bring clarity to your decisions. \n Leadership and Influence: Demonstrated ability to lead across a matrixed organization, align multiple stakeholders toward a common vision, and drive execution in a fast-paced, remote-first environment.   \n Communication Excellence: Outstanding spoken and written communication skills. You can distill complex engineering details into compelling narratives for both technical and non-technical audiences, including executive leadership.   \n Customer Obsession: A passion for industry trends and a commitment to solving real-world customer problems. You are an advocate for the developer persona and are dedicated to building products that empower users to innovate.\n Compensation for this role is in the form of base salary.  This role does not have a variable compensation component.   \n The typical starting salary range for new hires in this role is listed below.  In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below.  \n These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting.  We may ultimately pay more or less than the posted range, and the ranges may be modified in the future.   \n An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. \n Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program.  Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of","salary_min":191900,"salary_max":303500,"location":"United States","workplace":"remote","job_type":"full-time","experience_level":"principal","tags":["rag","agents","embeddings","llm","search","cloud"],"apply_url":"https://jobs.elastic.co/jobs?gh_jid=7940246\u0026gh_jid=7940246","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T15:40:24Z","expires_at":"2026-06-29T14:08:43.553707Z","created_at":"2026-05-27T14:08:57.755371Z","updated_at":"2026-05-30T14:08:43.662394Z","company_name":"Elastic","company_slug":"elastic","company_logo_url":"https://www.google.com/s2/favicons?domain=www.elastic.co\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b29b4009-8754-46c6-93f3-879cf9cf064a"},{"id":"b5fea2cb-9a9d-48e1-a093-60ed0dcc17d1","company_id":"308b7777-69e1-49db-ad79-3912d6c6e648","title":"Staff Software Engineer, Search","slug":"staff-software-engineer-search-11b04dec","description":"Our Mission \n Healthcare should work for patients, but it doesn’t. In their time of need, they call down outdated insurance directories. Then wait on hold. Then wait weeks for the privilege of a visit. Then wait in a room solely designed for waiting. Then wait for a surprise bill. In any other consumer industry, the companies delivering such a poor customer experience would not survive. But in healthcare, patients lack market power. Which means they are expected to accept the unacceptable. \n  \n Zocdoc’s mission is to give power to the patient. To do that, we’ve built the leading healthcare marketplace that makes it easy to find and book in-person or virtual care in all 50 states, across +200 specialties and +12k insurance plans. By giving patients the ability to see and choose, we give them power. In doing so, we can make healthcare work like every other consumer sector, where businesses compete for customers, not the other way around. In time, this will drive quality up and prices down.  \n  \n We’re 18 years old and the leader in our space, but we are still just getting started. If you like solving important, complex problems alongside deeply thoughtful, driven, and collaborative teammates, read on. \n  \n *Please note, we are open to remote candidates for this role. \n Your Impact on our Mission \n As a Staff Software Engineer on Zocdoc’s Search Services team, you will play a critical role in evolving one of the most important experiences we deliver to patients: helping them intuitively find and access the care that’s right for them. Our mission for 2026 and beyond is ambitious—we are transforming Zocdoc’s search function to an intelligent, intent-driven experience using embeddings, LLMs, and modern ranking models. This evolution requires rethinking our search architecture from the ground up, and delivering personalized, agentic flows that guide patients to care with unprecedented clarity and ease.\n You will lead the design and development of the high-performance backend services, APIs, and data infrastructure that make this vision possible. From our tier-1 search service and vector search systems to cross-encoder ranking pipelines, your work will power the intelligence behind Zocdoc Search. You’ll set the technical bar for backend engineering excellence while shaping the strategy of Zocdoc Search—helping unlock a new generation of intelligent, scalable, and patient-centered search infrastructure. \n You’ll enjoy this role if you are \n \n Passionate about building sophisticated backend systems — distributed services, data pipelines, and APIs that need to operate at scale with low latency and high reliability.\n Excited to architect the infrastructure powering intelligent search — from vector retrieval and cross-encoder reranking to real-time ingestion and indexing.\n Motivated by the challenge of integrating ML model serving, embeddings, and LLM-driven flows into production backend systems that serve millions of patients.\n A technical leader who thrives on architecting systems, mentoring engineers, and elevating code quality and team-wide execution\n  An excellent communicator who collaborates effectively with product, data science, and infrastructure partners.\n Energized by solving ambiguous infrastructure and architectural challenges to deliver elegant, robust solutions.\n \n Your day to day is… \n \n Architecting and building core backend services, APIs, and data infrastructure that power Zocdoc’s next-generation search platform.\n redesigning how provider, availability, and content data is ingested and flows through indexing pipelines into search and ML systems.\n Designing and optimizing low-latency query paths across our tier-1 search service, vector search infrastructure, and cross-encoder ranking systems.\n Integrating ML model serving, embedding generation, and ranking signals into production backend services through scalable, observable patterns.\n Driving architectural direction and setting engineering standards across the Search Services organization through design docs, technical deep dives, and high-signal code reviews.\n Mentoring engineers on backend best practices, distributed systems design, API architecture, and technical decision-making.\n Building robust observability into backend services—measuring, debugging, and improving performance, reliability, and data freshness across the entire search stack.\n \n You’ll be successful in this role if you have… \n \n A proven track record of owning and scaling complex, high-traffic backend platforms, with deep expertise in distributed systems design and long-term architectural thinking.\n Deep hands-on expertise with C# / .NET or comparable backend frameworks, with a focus on performance optimization, concurrency, and service-oriented architecture.\n Significant experience designing and operating large-scale data pipelines, ingestion systems, or stream-processing workflows.\n  Strong experience with AWS services and cloud-native","salary_min":211100,"salary_max":285000,"location":"New York, NY","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["agents","healthcare","distributed-systems","search","data-pipeline","mlops","cloud","llm"],"apply_url":"https://job-boards.greenhouse.io/zocdoc/jobs/7940003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-19T13:49:27Z","expires_at":"2026-06-29T14:18:25.39364Z","created_at":"2026-05-27T14:19:17.874752Z","updated_at":"2026-05-30T14:18:25.508421Z","company_name":"ZocDoc","company_slug":"zocdoc","company_logo_url":"https://www.google.com/s2/favicons?domain=zocdoc.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b5fea2cb-9a9d-48e1-a093-60ed0dcc17d1"},{"id":"9d1d550a-8f83-478f-9177-feb5d26a9adc","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Research Engineer, Voice + Speech","slug":"senior-research-engineer-voice-speech-1d2a6c12","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nRead more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs\n\n\nThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.\n\nOur goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.\n\n\n\nAbout the Role\n\nAs a Voice Research Engineer, you’ll lead the development of the models and algorithms that power Decagon’s industry-leading, real-time voice agents, and drive them all the way into production. You’ll own multi-quarter initiatives that advance speech understanding, naturalness, turn-taking, and resilience in real-world conditions. You’ll design and implement frontier approaches for training, evaluation, and orchestration across the voice agent.\n\nWe’re looking for strong engineers who want to build the core models and algorithms behind our AI agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.\n\n\n\nIn this role, you will\n\n - Lead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completion\n\n - Build and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experience\n\n - Partner with platform and product engineers to integrate new models into production systems\n\n - Break down ambiguous research ideas into clear, iterative milestones and roadmaps.\n\n - Mentor other researchers/engineers, set technical direction, and establish best practices for applied research and engineering\n\n\n\nYour background looks something like this\n\n - 5+ years of experience in AI/ML engineering or research.\n\n - Prior experience post-training and deploying LLMs in production environments.\n\n - Fluency in Python and modern ML tooling (training, evaluation, data pipelines)\n\n - Track record of taking research ideas from prototype → reliable, measurable production impact\n\n - Ability to define a roadmap, break ambiguity into milestones, and lead cross-functional execution\n\n\n\nCompensation\n\n$200K – $400K + Offers Equity\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Daily lunches and snacks in the office to keep you at your best\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":200000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["llm","search","agents","data-pipeline","research"],"apply_url":"https://jobs.ashbyhq.com/decagon/4a69b01d-6388-462a-8336-7cb288a87a0e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T17:36:47.593Z","expires_at":"2026-06-29T14:07:11.408162Z","created_at":"2026-05-27T14:07:26.70718Z","updated_at":"2026-05-30T14:07:11.53015Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9d1d550a-8f83-478f-9177-feb5d26a9adc"},{"id":"b0bfa86c-4df1-4aed-902b-42c14d691e34","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Staff Research Engineer, Voice + Speech","slug":"staff-research-engineer-voice-speech-86bf1ea2","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nRead more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs\n\n\nThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.\n\nOur goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.\n\n\n\nAbout the Role\n\nAs a Voice Research Engineer, you’ll lead the development of the models and algorithms that power Decagon’s industry-leading, real-time voice agents, and drive them all the way into production. You’ll own multi-quarter initiatives that advance speech understanding, naturalness, turn-taking, and resilience in real-world conditions. You’ll design and implement frontier approaches for training, evaluation, and orchestration across the voice agent.\n\nWe’re looking for strong engineers who want to build the core models and algorithms behind our AI agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.\n\n\n\nIn this role, you will\n\n - Lead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completion\n\n - Build and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experience\n\n - Partner with platform and product engineers to integrate new models into production systems\n\n - Break down ambiguous research ideas into clear, iterative milestones and roadmaps.\n\n - Mentor other researchers/engineers, set technical direction, and establish best practices for applied research and engineering\n\n\n\nYour background looks something like this\n\n - 8+ years of experience in AI/ML engineering or research.\n\n - Prior experience post-training and deploying LLMs in production environments.\n\n - Fluency in Python and modern ML tooling (training, evaluation, data pipelines)\n\n - Track record of taking research ideas from prototype → reliable, measurable production impact\n\n - Ability to define a roadmap, break ambiguity into milestones, and lead cross-functional execution\n\n\n\nCompensation\n\n$200K – $400K + Offers Equity\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Daily lunches and snacks in the office to keep you at your best\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":200000,"salary_max":400000,"location":"New York, NY","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","agents","search","llm","research"],"apply_url":"https://jobs.ashbyhq.com/decagon/73aca25c-a457-46fd-b4c4-9f76f356586c/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T17:36:18.4Z","expires_at":"2026-06-29T14:07:12.133794Z","created_at":"2026-05-27T14:07:27.384943Z","updated_at":"2026-05-30T14:07:12.250349Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b0bfa86c-4df1-4aed-902b-42c14d691e34"},{"id":"f592b426-3724-4841-b0a1-a776bfea768c","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Research Engineer, Voice + Speech","slug":"senior-research-engineer-voice-speech-6c1110f0","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nRead more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs\n\n\nThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.\n\nOur goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.\n\n\n\nAbout the Role\n\nAs a Voice Research Engineer, you’ll lead the development of the models and algorithms that power Decagon’s industry-leading, real-time voice agents, and drive them all the way into production. You’ll own multi-quarter initiatives that advance speech understanding, naturalness, turn-taking, and resilience in real-world conditions. You’ll design and implement frontier approaches for training, evaluation, and orchestration across the voice agent.\n\nWe’re looking for strong engineers who want to build the core models and algorithms behind our AI agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.\n\n\n\nIn this role, you will\n\n - Lead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completion\n\n - Build and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experience\n\n - Partner with platform and product engineers to integrate new models into production systems\n\n - Break down ambiguous research ideas into clear, iterative milestones and roadmaps.\n\n - Mentor other researchers/engineers, set technical direction, and establish best practices for applied research and engineering\n\n\n\nYour background looks something like this\n\n - 5+ years of experience in AI/ML engineering or research.\n\n - Prior experience post-training and deploying LLMs in production environments.\n\n - Fluency in Python and modern ML tooling (training, evaluation, data pipelines)\n\n - Track record of taking research ideas from prototype → reliable, measurable production impact\n\n - Ability to define a roadmap, break ambiguity into milestones, and lead cross-functional execution\n\n\n\nCompensation\n\n$200K – $400K + Offers Equity\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Daily lunches and snacks in the office to keep you at your best\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["llm","data-pipeline","agents","search","research"],"apply_url":"https://jobs.ashbyhq.com/decagon/4ec841cc-786c-459d-bf83-31b0071a85cc/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T17:16:48.759Z","expires_at":"2026-06-29T14:07:11.323265Z","created_at":"2026-05-27T14:07:26.635573Z","updated_at":"2026-05-30T14:07:11.44081Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f592b426-3724-4841-b0a1-a776bfea768c"},{"id":"9d392abd-0c8d-4aaf-8428-3f3281d435af","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Research Scientist, Wayve Labs","slug":"research-scientist-wayve-labs-158c2944","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The Role \n We’re looking for Research Scientists to join Wayve Labs and help build the next generation of AI systems for autonomous driving. You’ll work at the intersection of machine learning, simulation, robotics, and real-world deployment, contributing to core innovations that push the boundaries of embodied AI.\n Situated within Wayve, we are a high-conviction research team with the strategic patience and backing to prioritise multi-year breakthroughs over incremental gains. We are looking for highly motivated individuals with expertise and passion to push the frontier of embodied AI, including (but not limited to) the following areas:\n World \u0026 Reward Modeling: Building realistic, diverse simulators that can predict the consequences and costs of actions.\n Representation Learning \u0026 Spatial Intelligence: Advancing how machines truly understand and navigate dynamic, unstructured 3D environments, from detailed spatial understanding, to efficient long term memory.\n Scalable Decision-Making Systems: Designing architectures, reasoning systems, and policy learning algorithms that operate over long contexts, and scale with data and compute.\n Cross-Embodiment and Multimodal Learning: Advance embodied learning systems that can flexibly adapt to diverse robotic platforms and multimodal inputs, using vision, language, and active sensors.  \n Key Responsibilities \n \n Develop World Models and Planners (e.g., diffusion-based, autoregressive, or hybrid approaches) for realistic and consistent simulation\n Advance Reinforcement Learning and Reward Modeling, building scalable and safe learning frameworks across real and synthetic data\n Develop Geometric Foundation Models for 3D spatial understanding in dynamic, real-world environments.\n Enable Cross-Embodiment Robotics, leveraging the power of multimodal foundation models to accelerate robotic learning on diverse platforms.\n Conduct empirical research on Scaling laws, Generalisation, and Sim-to-real transfer\n Define and evolve Evaluation Frameworks and Benchmarks for long-horizon prediction, scene fidelity, and driving performance\n \n What You’ll Bring \n Must-haves:\n \n 3+ years of experience developing and deploying ML systems in real-world or production settings\n PhD, Master’s degree, or equivalent experience in Machine Learning, Computer Vision, Robotics, or a related field\n Deep expertise in one or more core Embodied AI areas, such as:\n \n Foundation models (e.g., transformers, MoE, large-scale training)\n Generative world modeling (e.g., diffusion, autoregressive, hybrid approaches)\n Reinforcement learning (e.g., offline RL, RLHF, reward modeling)\n Spatial AI (e.g., SLAM/SfM, depth estimation, multi-view geometry with multimodal sensors)\n \n Track record of publications at top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)\n Strong programming skills in Python, with experience using frameworks such as PyTorch\n A data-centric mindset, with experience working on large-scale datasets and evaluation\n Strong problem-solving ability and the ability to collaborate effectively in interdisciplinary teams\n \n Nice-to-haves:\n \n Experience in autonomous driving, robotics, or simulation systems\n Familiarity with large-scale training (e.g., FSDP, DeepSpeed, JAX)\n Experience with sim-to-real transfer or data-efficient learning\n Contributions to open-source ML tools or research infrastructure\n \n What we offer you  \n \n Attractive compensation with salary and equity \n Immersion in a team of world-class researchers, engineers and entrepreneurs \n A unique position to shape the future of autonomy and tackle the biggest challenge of our time \n Bespoke learning and development opportunities \n Relocation support with visa sponsorship \n Flexible working hours - we trust you to do your job well, at times that suit you and your time \n Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budge","salary_min":230000,"salary_max":380000,"location":"Sunnyvale, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["autonomous-vehicles","pytorch","computer-vision","generative-ai","robotics","reinforcement-learning","search","research"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8552567002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T04:48:53Z","expires_at":"2026-06-29T14:12:46.582695Z","created_at":"2026-05-27T14:13:10.467099Z","updated_at":"2026-05-30T14:12:46.693988Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9d392abd-0c8d-4aaf-8428-3f3281d435af"},{"id":"bef8e55e-fe6d-4a67-b298-d6a8b83d6b26","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Staff Frontier Agents Engineer","slug":"senior-staff-forward-deployed-ai-engineer-enterprise-c23669bc","description":"About Scale AI \n Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.\n Role Overview \n As a Senior Staff Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.\n This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.\n Key Responsibilities \n Customer Integration \u0026 Deployment \n \n Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements\n Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)\n Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows\n Deploy and configure AI models and agents within customer security and compliance boundaries\n \n AI Agent Development \n \n Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation\n Architect multi-agent systems that orchestrate between different models, tools, and data sources\n Implement evaluation frameworks to measure agent performance and iterate toward business objectives\n Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement\n \n Prompt Engineering \u0026 Optimization \n \n Create sophisticated prompt engineering strategies optimized for customer-specific domains and data\n Build and maintain prompt libraries, templates, and best practices for customer use cases\n Conduct systematic prompt experimentation and A/B testing to improve model outputs\n Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate\n \n Technical Leadership \u0026 Collaboration \n \n Serve as the primary technical point of contact for strategic enterprise accounts\n Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration\n Provide technical training and knowledge transfer to customer teams\n Work closely with Scale's product and engineering teams to translate customer needs into product improvements\n Document technical architectures, integration patterns, and best practices\n \n Problem Solving \u0026 Innovation \n \n Debug complex technical issues across the entire stack, from data pipelines to model outputs\n Rapidly prototype solutions to unblock customers and prove out new use cases\n Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems\n Identify opportunities for productization based on common customer patterns\n \n Required Qualifications \n \n 12+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design\n Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)\n Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure\n Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions\n Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences\n \n Preferred Qualifications \n Agent Development Wiz \n \n Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures\n Experience building and deploying AI agents or autonomous systems in production\n Knowledge of vector databases and semantic search systems\n Contributions to open-source AI/ML projects\n \n Infrastructure Guru \n \n Experience with containerization (Docker, Kubernetes) and CI/CD pipelines\n Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools\n Previous work in a devops, platform, or infra role\n Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)\n \n Customer Product Whisperer \n \n Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role\n Domain expertise in verticals like finance, healthcare, government, or manufacturing\n Experience with technical enablement or teaching programs\n \n Sample Projects \n The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer da","salary_min":288000,"salary_max":360000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["code-generation","healthcare","rag","search","llm","generative-ai","embeddings","agents"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4694869005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-15T23:55:32Z","expires_at":"2026-06-29T14:01:13.721439Z","created_at":"2026-05-16T14:01:23.031903Z","updated_at":"2026-05-30T14:01:13.834308Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bef8e55e-fe6d-4a67-b298-d6a8b83d6b26"},{"id":"ea24f46c-dc37-4f7b-a5f1-63431c79c43e","company_id":"a0000000-0000-0000-0000-000000000003","title":"Staff Frontier Agents Engineer ","slug":"staff-forward-deployed-ai-engineer-enterprise-c0df4021","description":"About Scale AI \n Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.\n Role Overview \n As a Staff Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.\n This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.\n Key Responsibilities \n Customer Integration \u0026 Deployment \n \n Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements\n Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)\n Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows\n Deploy and configure AI models and agents within customer security and compliance boundaries\n \n AI Agent Development \n \n Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation\n Architect multi-agent systems that orchestrate between different models, tools, and data sources\n Implement evaluation frameworks to measure agent performance and iterate toward business objectives\n Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement\n \n Prompt Engineering \u0026 Optimization \n \n Create sophisticated prompt engineering strategies optimized for customer-specific domains and data\n Build and maintain prompt libraries, templates, and best practices for customer use cases\n Conduct systematic prompt experimentation and A/B testing to improve model outputs\n Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate\n \n Technical Leadership \u0026 Collaboration \n \n Serve as the primary technical point of contact for strategic enterprise accounts\n Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration\n Provide technical training and knowledge transfer to customer teams\n Work closely with Scale's product and engineering teams to translate customer needs into product improvements\n Document technical architectures, integration patterns, and best practices\n \n Problem Solving \u0026 Innovation \n \n Debug complex technical issues across the entire stack, from data pipelines to model outputs\n Rapidly prototype solutions to unblock customers and prove out new use cases\n Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems\n Identify opportunities for productization based on common customer patterns\n \n Required Qualifications \n \n 8+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design\n Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)\n Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure\n Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions\n Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences\n \n Preferred Qualifications \n Agent Development Wiz \n \n Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures\n Experience building and deploying AI agents or autonomous systems in production\n Knowledge of vector databases and semantic search systems\n Contributions to open-source AI/ML projects\n \n Infrastructure Guru \n \n Experience with containerization (Docker, Kubernetes) and CI/CD pipelines\n Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools\n Previous work in a devops, platform, or infra role\n Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)\n \n Customer Product Whisperer \n \n Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role\n Domain expertise in verticals like finance, healthcare, government, or manufacturing\n Experience with technical enablement or teaching programs\n \n Sample Projects \n The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, inte","salary_min":252000,"salary_max":315000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["embeddings","llm","healthcare","search","data-pipeline","fine-tuning","rag","code-generation"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4694865005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-15T23:54:36Z","expires_at":"2026-06-29T14:01:14.746596Z","created_at":"2026-05-16T14:01:24.232193Z","updated_at":"2026-05-30T14:01:14.857364Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ea24f46c-dc37-4f7b-a5f1-63431c79c43e"},{"id":"52eb01bc-eaeb-4d71-b23c-063d99529ee2","company_id":"91fe6e70-08c8-4174-9ea8-4df901ae72f3","title":"Senior Product Manager","slug":"senior-product-manager-43da43d5","description":"About Us \n At You.com, we are building the AI Search Infrastructure that powers modern AI systems. Our goal is to create the trusted knowledge layer that agents, applications, and enterprises rely on to retrieve real-time, accurate, and citation-backed information.\n Our platform combines proprietary vertical indexes with LLM-optimized retrieval systems to power AI agents, applications, and enterprise workflows. We are solving hard problems across search, large language models, and large-scale infrastructure to make AI systems more reliable, transparent, and useful.\n Our team includes engineers, researchers, product builders, and operators who care about solving meaningful problems and delivering real-world impact. Whether you are improving core infrastructure, shaping product experiences, or helping bring new AI capabilities to market, your work will help define how modern AI finds and uses knowledge.\n About the Role\n AI applications differ widely in what they need from the web. A legal AI needs exhaustive coverage of case law. A competitive intelligence platform needs hourly refresh on competitor pricing. A financial AI agent needs real-time market data fused with news. A general web index gives all of them the same thing. We're building something better.\n We are looking for a Product Manager to lead our  AI Web Infrastructure product line: domain-specific, deeply crawled, high-freshness data infrastructure built for AI-native companies with premium accuracy and coverage requirements. This is greenfield product work at the intersection of search infrastructure, data engineering, and the agentic AI wave.\n You will own the roadmap for how we go deep in specific verticals (financial data, news, legal, and beyond) and how we expose that infrastructure as API products customers can build on. You'll work directly with engineering on crawl architecture, ranking models, and eval frameworks; directly with customers and BD to close and onboard design partners; and across the company to define what AI web infrastructure means as a product category.\n This is an entirely new product category in the AI space – one that is already operating at enterprise production scale for demanding customers. This role is for someone who has done this work directly (web infrastructure, search systems, large-scale crawl and indexing pipelines) or has strong adjacent experience (ML infrastructure, data pipelines, eval systems, LLM products). Either path prepares you well.\n  \n What You'll Do\n \n Own the vision, strategy, and roadmap for AI web infrastructure products, from initial design-partner scoping through production deployment and scale\n Define what domain-specific web infrastructure means as a product: crawl depth, freshness requirements, ranking models, data fusion, and the API surface customers interact with\n Lead the full product development lifecycle for new vertical index APIs: discovery, scoping, specification, launch, and iteration\n Partner with engineering to define crawl architecture, extraction pipelines, ranking approaches, and performance SLAs for each vertical\n Build and run the eval framework for vertical indexes: customer-provided eval sets, ROI metrics, and case study development\n Work directly with BD and Sales to scope design-partner deals, translate customer requirements into product specs, and support closing\n Conduct market analysis on vertical data needs, competitive offerings, and emerging AI application requirements\n Track and improve key metrics: coverage completeness, freshness delta, ranking quality, API latency, and customer satisfaction\n \n  \n What We're Looking For\n Required: \n \n 5+ years in product management, with significant experience owning API-driven data products, data infrastructure, or large-scale data pipelines\n Strong technical foundation: able to reason deeply about crawl architecture, data pipelines, ranking systems, and API design\n Experience with evaluation frameworks: defining ground truth, designing benchmarks, and measuring quality rigorously\n Track record of shipping at speed in ambiguous, fast-moving environments; startup experience strongly preferred\n Exceptional written and verbal communication: able to produce a crisp product spec, a customer-facing pitch, and an engineering design doc\n \n Strongly Preferred: \n \n Background in ML infrastructure, data quality, or LLM evaluation; or direct experience building web-scale systems (crawling, extraction, indexing, or ranking)\n Experience with web infrastructure at scale: crawl pipelines, index architecture, or search ranking systems\n Familiarity with the AI search infrastructure landscape and agentic AI application patterns\n Experience working with enterprise customers on bespoke data requirements\n \n  \n Why This Role\n \n Greenfield. AI web infrastructure is a new product line. You're defining the category from the ground up.\n Technically deep. This is real infrastructure work on hard, unsolved problems.\n Agentic timing. The shift fro","salary_min":200000,"salary_max":250000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","api-design","payments","llm","data-pipeline","search"],"apply_url":"https://job-boards.greenhouse.io/youcom/jobs/5222711008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-15T21:17:03Z","expires_at":"2026-06-29T14:17:53.226521Z","created_at":"2026-05-16T14:18:40.616851Z","updated_at":"2026-05-30T14:17:53.343634Z","company_name":"You.com","company_slug":"you-com","company_logo_url":"https://www.google.com/s2/favicons?domain=you.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/52eb01bc-eaeb-4d71-b23c-063d99529ee2"}],"page":1,"per_page":20,"total":717,"total_pages":36}