{"has_next":true,"jobs":[{"id":"60c7aa2a-21b2-4ed4-997e-01e06f7425d0","company_id":"a0000000-0000-0000-0000-000000000003","title":"Director, Enterprise Machine Learning \u0026 Research","slug":"director-enterprise-machine-learning-research-1923b033","description":"The Enterprise ML team works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale’s proprietary research, data, and infrastructure—unlocking domain expertise through high-quality data and expert feedback.\n As Director of Enterprise ML, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.\n This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems.\n What You’ll Do \n \n Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).  \n Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.\n Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.\n Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.\n Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.\n Stay deeply connected to the research community, understanding major trends, and helping set them.\n Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.\n \n What We’re Looking For \n Core Qualifications \n \n 8+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.\n A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).\n Experience and track of recording in landing major research impacts in a fast-paced environment\n Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.\n Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.\n Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners\n \n Nice to Have \n \n Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments\n Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale\n Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes\n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:\n $289,800 — $362,250 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with","salary_min":289800,"salary_max":362250,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["deep-learning","llm","generative-ai","machine-learning","research"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4679727005","is_featured":true,"is_sticky":false,"status":"active","published_at":"2026-03-31T18:05:38Z","expires_at":"2026-06-29T14:01:07.494675Z","created_at":"2026-04-13T09:36:42.207592Z","updated_at":"2026-05-30T14:01:07.606238Z","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/60c7aa2a-21b2-4ed4-997e-01e06f7425d0"},{"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":"3e448289-7fed-4d06-9da9-bd0879a8241b","company_id":"a0000000-0000-0000-0000-000000000003","title":"Manager, Machine Learning Research Scientist, GenAI","slug":"manager-machine-learning-research-scientist-genai-c7602476","description":"Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications.\n As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.\n As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.\n You will: \n \n Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).  \n Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.\n Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.\n Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.\n Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.\n Stay deeply connected to the research community, understanding major trends, and helping set them.\n Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.\n \n Ideally you'd have: \n \n 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.\n A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).\n Experience and track of recording in landing major research impacts in a fast-paced environment\n Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.\n Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.\n \n \n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:\n $398,400 — $498,000 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. \n We believe that everyone ","salary_min":398400,"salary_max":498000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","generative-ai","deep-learning","machine-learning","research"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4631811005","is_featured":true,"is_sticky":false,"status":"active","published_at":"2025-11-19T00:07:25Z","expires_at":"2026-06-29T14:01:10.349946Z","created_at":"2026-04-13T09:36:44.631119Z","updated_at":"2026-05-30T14:01:10.459208Z","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/3e448289-7fed-4d06-9da9-bd0879a8241b"},{"id":"c47d445d-a8c4-46a7-815e-584f4ff1b92b","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Research Scientist - Frontier Benchmarks","slug":"research-scientist-frontier-benchmarks-83166d4b","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n \n \n ABOUT THE ROLE  \n We're looking for a Research Scientist to collaborate with partners and lead the development of the next frontier benchmarks and datasets. This is a highly visible, customer-facing role at the intersection of research, company strategy, and go-to-market. You'll design datasets taking into account frontier model performance and work with our academic partners, and then partner with delivery, product and go-to-market to scale out production. You will also  serve as a credible technical partner for our customers, prospects, and drive results that impact the broader research community. \n This role reports directly to the Head of Research and is ideal for someone who is energized by cross-functional work and wants to understand how startups operate across research, data operations, and commercial teams. \n MAIN RESPONSIBILITIES  \n \n Design state of the art datasets that drive frontier model training and evaluation based on current model performance and academic partnerships \n Translate benchmark insights into clear, compelling narratives that articulate the ROI of expert-curated data for customer-facing presentations, technical reports, and go-to-market materials.\n Work cross-functionally with data operations, product, engineering, and strategy to surface research findings that inform the company roadmap. \n Stay at the frontier of LLM evaluation research and bring best practices into Snorkel's workflows\n Represent Snorkel's research externally through publications, blog posts, conference talks, and customer engagements that advance the conversation around data-centric AI\n \n PREFERRED QUALIFICATIONS  \n \n Strong research background in AI/ML evaluation, NLP, or related fields, with a track record of rigorous experimental design — especially around measuring the impact of training and evaluation data on model behavior. \n Exceptional communication skills — able to present complex technical findings clearly to both technical and non-technical audiences \n Comfort operating in a fast-moving, cross-functional environment with ambiguous problem spaces \n Genuine interest in GTM strategy, startup dynamics, and the commercial side of AI data services. \n Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.\n \n \n  \n Salary Range \n $200,000 — $325,000 USD \n Be Your Best at Snorkel \n Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.\n Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. \n We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.","salary_min":200000,"salary_max":325000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["llm","generative-ai","nlp","research"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6009489004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T21:19:29Z","expires_at":"2026-06-29T14:03:05.663367Z","created_at":"2026-05-30T14:03:05.781019Z","updated_at":"2026-05-30T14:03:05.781019Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c47d445d-a8c4-46a7-815e-584f4ff1b92b"},{"id":"55cd3fa3-a9a4-4e85-8ee6-328ca1be5a54","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior Research Scientist ","slug":"senior-research-scientist-446bc234","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n Anduril’s Research Scientists excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our research scientists build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Therefore, Anduril is seeking talented “magicians” to join in our common struggle of expanding the boundary of what’s possible.\n WHAT YOU WILL DO: \n \n Contribute to the direction of a talented small team with your expertise and ideas;\n Create mathematically principled solutions to some of the world’s most challenging information science problems;\n Prototype state-of-the-art algorithms in an agile development environment;\n Implement high-performance software spanning the spectrum from tactical systems to web applications;\n Use high-fidelity modeling and simulation environments, innovative analysis tools, and flexible compute clusters to quantify the benefit of our technology;\n Engage with our customers, to ensure successful outcomes for their mission-critical needs;\n Help your colleagues and customers understand what you’re doing and why.\n \n REQUIRED QUALIFICATIONS: \n \n A Research Scientist at Anduril should possess an M.S. or Ph.D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field.\n Experience coding languages with Rust, C++, and Python.\n A Research Scientist should have a record of academic excellence, including demonstrated experience in most of the following areas:\n \n Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;\n Engineering: controls, estimation theory, digital signal processing, and machine learning;\n Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;\n Probability: statistics and random processes.\n \n A Research Scientist should have effective written and verbal communication skills, with the demonstrated ability to convey salient details about advanced technology in a compelling manner to both experts and non-experts alike.\n Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance\n \n We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment. \n US Salary Range\n $190,000 — $252,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and what","salary_min":190000,"salary_max":252000,"location":"Broomfield, CO","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["payments","computer-vision","cloud","research"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5150395007?gh_jid=5150395007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T18:57:01Z","expires_at":"2026-06-29T14:06:50.575027Z","created_at":"2026-05-30T14:06:50.69205Z","updated_at":"2026-05-30T14:06:50.69205Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/55cd3fa3-a9a4-4e85-8ee6-328ca1be5a54"},{"id":"d37cc854-47d3-4768-bb06-13c027f4cb0d","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior Research Scientist","slug":"senior-research-scientist-9894e287","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n Anduril’s Research Scientists excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our research scientists build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Therefore, Anduril is seeking talented “magicians” to join in our common struggle of expanding the boundary of what’s possible.\n WHAT YOU WILL DO: \n \n Contribute to the direction of a talented small team with your expertise and ideas;\n Create mathematically principled solutions to some of the world’s most challenging information science problems;\n Prototype state-of-the-art algorithms in an agile development environment;\n Implement high-performance software spanning the spectrum from tactical systems to web applications;\n Use high-fidelity modeling and simulation environments, innovative analysis tools, and flexible compute clusters to quantify the benefit of our technology;\n Engage with our customers, to ensure successful outcomes for their mission-critical needs;\n Help your colleagues and customers understand what you’re doing and why.\n \n REQUIRED QUALIFICATIONS: \n \n A Research Scientist at Anduril should possess an M.S. or Ph.D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field.\n Experience coding languages with Rust, C++, and Python.\n A Research Scientist should have a record of academic excellence, including demonstrated experience in most of the following areas:\n \n Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;\n Engineering: controls, estimation theory, digital signal processing, and machine learning;\n Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;\n Probability: statistics and random processes.\n \n A Research Scientist should have effective written and verbal communication skills, with the demonstrated ability to convey salient details about advanced technology in a compelling manner to both experts and non-experts alike.\n Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance\n \n We request transcripts as part of the early application process to understand your academic background and how your coursework supports the skills deemed critical for the role. Transcripts help us assess your technical and analytical abilities, complementing our interview process in which we also evaluate practical experience and cultural fit. If you choose not to share your transcripts, you will need to provide detailed information regarding your academic performance in relevant courses, including projects and coursework specifics, to ensure we evaluate your academic accomplishments properly. If you do provide academic transcripts, feel free to redact non-technical information (e.g., student ID, dates, non-technical coursework, etc.). Unofficial transcripts obtained online acceptable for this assessment. \n US Salary Range\n $190,000 — $252,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and what","salary_min":190000,"salary_max":252000,"location":"Fort Collins, CO","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["payments","computer-vision","cloud","research"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5150393007?gh_jid=5150393007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T18:57:01Z","expires_at":"2026-06-29T14:06:50.412308Z","created_at":"2026-05-30T14:06:50.532789Z","updated_at":"2026-05-30T14:06:50.532789Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d37cc854-47d3-4768-bb06-13c027f4cb0d"},{"id":"4d4aaea0-d65f-4984-a467-68828e91e16b","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Research Scientist","slug":"research-scientist-03c490d7","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n Anduril’s Research Scientists excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our research scientists build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Therefore, Anduril is seeking talented “magicians” to join in our common struggle of expanding the boundary of what’s possible.\n WHAT YOU WILL DO : \n \n Contribute to the direction of a talented small team with your expertise and ideas;\n Create mathematically principled solutions to some of the world’s most challenging information science problems;\n Prototype state-of-the-art algorithms in an agile development environment;\n Implement high-performance software spanning the spectrum from tactical systems to web applications;\n Use high-fidelity modeling and simulation environments, innovative analysis tools, and flexible compute clusters to quantify the benefit of our technology;\n Engage with our customers, to ensure successful outcomes for their mission-critical needs;\n Help your colleagues and customers understand what you’re doing and why.\n \n REQUIRED QUALIFICATIONS: \n \n A Research Scientist at Anduril should possess an M.S. or Ph.D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field.\n A Research Scientist should have a record of academic excellence, including demonstrated experience in most of the following areas:\n \n Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;\n Engineering: controls, estimation theory, digital signal processing, and machine learning;\n Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;\n Probability: statistics and random processes.\n \n A Research Scientist should have effective written and verbal communication skills, with the demonstrated ability to convey salient details about advanced technology in a compelling manner to both experts and non-experts alike.\n Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance\n US Salary Range\n $165,000 — $218,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:\n \n \n No Financial Requests:  Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment ","salary_min":165000,"salary_max":218000,"location":"Broomfield, CO","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["cloud","computer-vision","payments","research"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5150299007?gh_jid=5150299007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T18:05:13Z","expires_at":"2026-06-29T14:06:46.452393Z","created_at":"2026-05-30T14:06:46.569518Z","updated_at":"2026-05-30T14:06:46.569518Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4d4aaea0-d65f-4984-a467-68828e91e16b"},{"id":"2d08c87b-e684-477c-8ede-d52b9306fde1","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Research Scientist","slug":"research-scientist-9aa05d5e","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n Anduril’s Research Scientists excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our research scientists build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Therefore, Anduril is seeking talented “magicians” to join in our common struggle of expanding the boundary of what’s possible.\n WHAT YOU WILL DO : \n \n Contribute to the direction of a talented small team with your expertise and ideas;\n Create mathematically principled solutions to some of the world’s most challenging information science problems;\n Prototype state-of-the-art algorithms in an agile development environment;\n Implement high-performance software spanning the spectrum from tactical systems to web applications;\n Use high-fidelity modeling and simulation environments, innovative analysis tools, and flexible compute clusters to quantify the benefit of our technology;\n Engage with our customers, to ensure successful outcomes for their mission-critical needs;\n Help your colleagues and customers understand what you’re doing and why.\n \n REQUIRED QUALIFICATIONS: \n \n A Research Scientist at Anduril should possess an M.S. or Ph.D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field.\n A Research Scientist should have a record of academic excellence, including demonstrated experience in most of the following areas:\n \n Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;\n Engineering: controls, estimation theory, digital signal processing, and machine learning;\n Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;\n Probability: statistics and random processes.\n \n A Research Scientist should have effective written and verbal communication skills, with the demonstrated ability to convey salient details about advanced technology in a compelling manner to both experts and non-experts alike.\n Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance\n US Salary Range\n $165,000 — $218,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:\n \n \n No Financial Requests:  Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment ","salary_min":165000,"salary_max":218000,"location":"Fort Collins, CO","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["cloud","payments","computer-vision","research"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5150296007?gh_jid=5150296007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T18:04:40Z","expires_at":"2026-06-29T14:06:46.536204Z","created_at":"2026-05-30T14:06:46.647508Z","updated_at":"2026-05-30T14:06:46.647508Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2d08c87b-e684-477c-8ede-d52b9306fde1"},{"id":"79614b75-dd99-448d-a2a2-5a1ebca21536","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Research Scientist","slug":"research-scientist-5f357ff4","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n Anduril’s Research Scientists excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our research scientists build solutions that make a difference. Our research endeavors don’t end once we’ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic.” Therefore, Anduril is seeking talented “magicians” to join in our common struggle of expanding the boundary of what’s possible.\n WHAT YOU WILL DO : \n \n Contribute to the direction of a talented small team with your expertise and ideas;\n Create mathematically principled solutions to some of the world’s most challenging information science problems;\n Prototype state-of-the-art algorithms in an agile development environment;\n Implement high-performance software spanning the spectrum from tactical systems to web applications;\n Use high-fidelity modeling and simulation environments, innovative analysis tools, and flexible compute clusters to quantify the benefit of our technology;\n Engage with our customers, to ensure successful outcomes for their mission-critical needs;\n Help your colleagues and customers understand what you’re doing and why.\n \n REQUIRED QUALIFICATIONS: \n \n A Research Scientist at Anduril should possess an M.S. or Ph.D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field.\n A Research Scientist should have a record of academic excellence, including demonstrated experience in most of the following areas:\n \n Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;\n Engineering: controls, estimation theory, digital signal processing, and machine learning;\n Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;\n Probability: statistics and random processes.\n \n A Research Scientist should have effective written and verbal communication skills, with the demonstrated ability to convey salient details about advanced technology in a compelling manner to both experts and non-experts alike.\n Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance\n US Salary Range\n $165,000 — $218,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:\n \n \n No Financial Requests:  Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment ","salary_min":165000,"salary_max":218000,"location":"Huntsville, Alabama, United States","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["payments","cloud","computer-vision","research"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5150279007?gh_jid=5150279007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T17:56:23Z","expires_at":"2026-06-29T14:06:46.695118Z","created_at":"2026-05-30T14:06:46.806824Z","updated_at":"2026-05-30T14:06:46.806824Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/79614b75-dd99-448d-a2a2-5a1ebca21536"},{"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":"41b3afd9-e8d0-4d82-9e8e-9149ad7c9147","company_id":"0bedcaf4-210e-4f52-95d5-a82be8aff446","title":"Sr Machine Learning Engineer, AI Research","slug":"sr-machine-learning-engineer-ai-research-866a2680","description":"Join the company that’s building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world’s biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what’s next.\n We’re one of the fastest‑growing private companies and a leading player in a massive, fast‑moving market. With a global workforce, we’re remote‑first and grounded in a simple idea: software is a people business. Cribl is the place where curious, collaborative people can do their best work, grow fast, and bring their full selves to the herd.\n Why You'll Love This Role \n You will work closely with the founding team and a group of highly-skilled engineers to shape the future of AI-enabled Security/Observability platforms. You will play a central role in bringing integrating cutting-edge AI/ML technologies to the Cribl Product suite to help solve real customer problems.  You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers.\n On top of it all you will have fun. \n Cribl strives to be a great place to work for everyone.\n As An Active Member Of Our Team, You Will... \n \n Design, train, and evaluate machine learning models across a range of research and applied AI initiatives\n Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements\n Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems\n Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation\n Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation\n Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team\n Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them\n This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones\n \n If You've Got It - We Want It \n \n Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 4+ years of industry or research experience (Master's or PhD a plus)\n Deep hands-on experience training and evaluating ML models, including language models\n Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow\n Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights \u0026 Biases, Kubeflow, or similar)\n Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques\n Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize\n Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders\n \n #LI-Tag #LI-Remote\n The salary for this role is dependent on geographic location and will be based on the individual candidate's job-related knowledge, skills, and experience. In addition to base salary, for sales and some sales-adjacent roles, employees are eligible to earn incentive compensation (commission). For all other roles, employees are eligible to participate in the Cribl Corporate Bonus Program. In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), and equity.\n Base Salary Range\n $185,000 — $215,000 USD \n Bring Your Whole Self Diversity drives innovation, enables better decisions to support our customers, and inspires change for the better. We’re building a culture where differences are valued and welcomed, and we work together to bring out the best in each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying. \n Interested in joining the Cribl herd? Learn more about the smartest, funniest, most passionate goats you’ll ever meet at cribl.io/about-us .","salary_min":185000,"salary_max":215000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["nlp","tensorflow","computer-vision","mlops","pytorch","reinforcement-learning","fine-tuning","research"],"apply_url":"https://cribl.io/job-detail/?gh_jid=5979543004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T18:02:31Z","expires_at":"2026-06-29T14:18:07.512926Z","created_at":"2026-05-28T14:19:42.491471Z","updated_at":"2026-05-30T14:18:07.623902Z","company_name":"Cribl","company_slug":"cribl","company_logo_url":"https://www.google.com/s2/favicons?domain=cribl.io\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/41b3afd9-e8d0-4d82-9e8e-9149ad7c9147"},{"id":"83ca8ffa-09ac-4942-a639-4e6c4b482642","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, Operations Research","slug":"senior-software-engineer-operations-research-e517b660","description":"Your Impact at LILA \n We are a cross-functional team (Software and Robotics) developing orchestration algorithms (instrument scheduling and robot routing) and lab simulation capabilities. We are building the muscles of the lab, which translate the AI brain's ideas into efficient robotic movements. Our work involves building data pipelines to feed the orchestration algorithms. We work with robotics scientists to build and deploy the algorithms on our software platform and ensure they meet scientific constraints.\n We are seeking a Senior Software Engineer, Operations Research to join our software group and help build the next generation AI-driven scientific platform. In this role, you will design, build, and optimize backend systems and data infrastructure that power orchestration and lab execution. You will focus on developing services, high-performance APIs, databases, and ensuring the reliability of systems that integrate advanced AI frameworks with complex scientific workflows.\n You'll work closely with robotics researchers, platform engineers, and scientists to develop systems that can handle diverse workloads and scale to demanding throughput. This is an opportunity to apply your engineering expertise to a cutting-edge AI platform with real scientific impact. If you are passionate about building performant and elegant systems, we would love to hear from you.\n What You'll Be Building \n \n (Fleet) orchestrator, Scheduler, Manufacturing Execution System, data pipelines, and related software systems.\n Design \u0026 Build APIs: Design and build APIs and backend services that integrate with AI-driven applications, with focus on reliability and performance.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Build and deploy production-grade systems on AWS using Kubernetes and modern DevOps practices.\n Cross-Functional Collaboration: Work with robotics scientists, platform engineers, and ML teams to integrate data pipelines and orchestration into scientific workflows.\n \n What You'll Need to Succeed \n \n Bachelor's or Master's degree in Computer Science, Engineering, or related field.\n 5–10 years of engineering experience building and deploying large-scale backend or data systems in production.\n Backend / Data Development: Experience developing distributed software and data systems (Postgres, Flyte, Temporal, NATS/MQTT, FastAPI).\n Hands-on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Experience developing scheduling software or manufacturing execution systems.\n Experience with operations research solvers (OR-Tools, HiGHS, Gurobi).\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Familiarity with Python for Science: Familiarity with data science, data visualization, and ML libraries (pandas, polars, numpy, scipy, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $180,000 — $256,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA bui","salary_min":180000,"salary_max":256000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["pytorch","robotics","cloud","data-pipeline","embeddings","research"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4246973009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:22:46Z","expires_at":"2026-06-29T14:17:43.904427Z","created_at":"2026-05-27T14:18:35.008145Z","updated_at":"2026-05-30T14:17:44.01629Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/83ca8ffa-09ac-4942-a639-4e6c4b482642"},{"id":"b40b33bc-6868-4ebb-ac4d-e56f85f945a1","company_id":"a355eb2f-63c3-4c0a-803d-bc2d8312b6d8","title":"Researcher, Context - Agent Post-Training","slug":"researcher-context-agent-post-training-528ac150","description":"About the Team\n\nThe Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve.\n\nWe define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste.\n\nOur team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use.\n\n\n\nAbout the Role\n\nWe believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models.\n\n\n\nIn this role, you will:\n\n - Design and run experiments that improve scaling of compute on context.\n\n - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.\n\n - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions.\n\n - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements.\n\n - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior.\n\n - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.\n\n - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.\n\n - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments.\n\n - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes.\n\n\n\nYou might thrive in this role if you:\n\n - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before.\n\n - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.\n\n - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution.\n\n - Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with.\n\n - Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next.\n\n - Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group.\n\n - Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous.\n\n - Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users.\n\n\n\nCompensation Range: $250K - $380K USD\n\n\n\nAbout OpenAI\n\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. \n\nWe are an equal opportunity employer, and we do n","salary_min":250000,"salary_max":380000,"location":"San Francisco, CA","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","llm","agents","reinforcement-learning","research"],"apply_url":"https://jobs.ashbyhq.com/openai/5b1394e6-e133-4dc0-97aa-87a91e5d1b52/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T23:08:33.816Z","expires_at":"2026-06-29T14:01:00.439954Z","created_at":"2026-05-27T14:01:09.912882Z","updated_at":"2026-05-30T14:01:00.551597Z","company_name":"OpenAI","company_slug":"openai","company_logo_url":"https://www.google.com/s2/favicons?domain=openai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b40b33bc-6868-4ebb-ac4d-e56f85f945a1"},{"id":"be23cbd4-5c9a-484b-a887-06083ee99bd5","company_id":"a355eb2f-63c3-4c0a-803d-bc2d8312b6d8","title":"Researcher, Connectors - Agent Post-Training","slug":"researcher-connectors-agent-post-training-e5a1f5ce","description":"About the Team\n\nThe Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve.\n\nWe define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste.\n\nOur team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use.\n\n\n\nAbout the Role\n\nAs a member of Agent Post-Training, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use.\n\nYou will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models.\n\n\n\nIn this role, you will:\n\n - Design and run experiments that improve agentic model behavior for complex software and plugins.\n\n - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.\n\n - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions.\n\n - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements.\n\n - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior.\n\n - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.\n\n - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.\n\n - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments.\n\n - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes.\n\n\n\nYou might thrive in this role if you:\n\n - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before.\n\n - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.\n\n - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution.\n\n - Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with.\n\n - Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next.\n\n - Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group.\n\n - Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous.\n\n - Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users.\n\nCompensation Ranges: $250K - $380K USD\n\n\n\nAbout OpenAI\n\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligen","salary_min":250000,"salary_max":380000,"location":"San Francisco, CA","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["llm","agents","data-pipeline","reinforcement-learning","research"],"apply_url":"https://jobs.ashbyhq.com/openai/d55af855-0d7b-4407-a27d-5fa9f894382c/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T23:08:05.419Z","expires_at":"2026-06-29T14:01:00.206702Z","created_at":"2026-05-27T14:01:09.65114Z","updated_at":"2026-05-30T14:01:00.312483Z","company_name":"OpenAI","company_slug":"openai","company_logo_url":"https://www.google.com/s2/favicons?domain=openai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/be23cbd4-5c9a-484b-a887-06083ee99bd5"},{"id":"c8a45766-54d1-4818-ae4d-b8b7b937c1ae","company_id":"a355eb2f-63c3-4c0a-803d-bc2d8312b6d8","title":"Researcher, Artifacts - Agent Post-Training","slug":"researcher-artifacts-agent-post-training-0388a47d","description":"About the Team\n\nThe Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve.\n\nWe define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste.\n\nOur team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use.\n\n\n\nAbout the Role\n\nAs a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis.\n\nYou will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models.\n\n\n\nIn this role, you will:\n\n - Design and run experiments that improve agentic model behavior for complex software and plugins..\n\n - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.\n\n - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions.\n\n - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements.\n\n - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior.\n\n - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.\n\n - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.\n\n - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments.\n\n - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes.\n\n\n\nYou might thrive in this role if you:\n\n - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before.\n\n - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.\n\n - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution.\n\n - Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with.\n\n - Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next.\n\n - Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group.\n\n - Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous.\n\n - Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users.\n\n - Have some prior background in consulting, finance, marketing, operations, or data science.\n\n\n\nCompensation Range: $250K - $380K USD\n\n\n\nAbout OpenAI\n\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safel","salary_min":250000,"salary_max":380000,"location":"San Francisco, CA","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","agents","llm","reinforcement-learning","research"],"apply_url":"https://jobs.ashbyhq.com/openai/c701bf4a-3b17-4b14-895a-05f52be51cf8/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T23:06:48.091Z","expires_at":"2026-06-29T14:01:00.2812Z","created_at":"2026-05-27T14:01:09.751126Z","updated_at":"2026-05-30T14:01:00.393142Z","company_name":"OpenAI","company_slug":"openai","company_logo_url":"https://www.google.com/s2/favicons?domain=openai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c8a45766-54d1-4818-ae4d-b8b7b937c1ae"},{"id":"42f8830a-ebfa-421c-a5b0-188eb93d4cd8","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Applied Research Scientist, Multi-Modal Perception (PhD New Grad)","slug":"applied-research-scientist-multi-modal-perception-phd-new-grad-74815077","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.\n In this hybrid role you will report to a Technical Lead Manager.\n You will: \n \n Own tasks in the ML Driver, take responsibility for task scaling and task performance, create ML methods and recipes to scale and improve tasks.\n Analyze behavior of ML systems in real-world application, identify issues and root causes, advise or develop short- and long-term solutions.\n Monitor ML systems in production, develop methods for automatically detecting issues or regressions, develop AI-aided analysis and debugging tooling.\n Develop and maintain metrics for ADV relevant issues, including safety-critical and longtail issues.\n \n You have: \n \n Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience\n 3+ years experience in Machine Learning and Computer Vision\n Experience with Python\n Experience with ML frameworks like PyTorch or JAX\n \n We prefer: \n \n MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline\n Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI\n Experience with C++\n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $175,000 — $215,000 USD","salary_min":175000,"salary_max":215000,"location":"Mountain View, CA","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["computer-vision","autonomous-vehicles","pytorch","deep-learning","robotics","research"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=7948348","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-20T23:48:38Z","expires_at":"2026-06-29T14:04:23.835364Z","created_at":"2026-05-27T14:04:33.548406Z","updated_at":"2026-05-30T14:04:23.954594Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/42f8830a-ebfa-421c-a5b0-188eb93d4cd8"},{"id":"a62cc613-162e-4779-81ca-502537d39185","company_id":"a0000000-0000-0000-0000-000000000001","title":"Performance Engineer, Inference Systems","slug":"performance-engineer-inference-systems-d02d5600","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the Role \n Anthropic's inference fleet serves Claude to millions of users across our own products and the world's largest cloud platforms. The stack that makes this possible is deep and tightly coupled: accelerator kernels, model servers, distributed routing, autoscaling, capacity management. Every layer affects the others, often in ways that are hard to see in isolation.\n The Inference System Dynamics team is responsible for understanding that whole system and holding it to a high bar across four dimensions: throughput, latency, reliability, and correctness . We measure how the fleet performs against its theoretical performance frontier, run cross-layer investigations to explain the gaps, and own the correctness checks that make sure Claude's outputs are right, not just fast, across hardware platforms and serving configurations. We don't own the individual components. We instrument and model them, find the highest-leverage opportunities across them, and partner with the owning teams to land the wins.\n You'll work across all four areas. One week that might mean tracing a tail-latency regression from request timing down through routing and batching into a kernel overhead; the next it might mean tightening a correctness eval so it catches an output regression introduced by a quantization change. We're looking for performance engineers who treat correctness as part of performance.\n Key Responsibilities \n \n Run cross-layer performance investigations across throughput, latency, and reliability, sizing the gap between actual fleet performance and theoretical rooflines, identifying root causes, and quantifying the value of closing them\n Own and improve the correctness evaluation pipeline that validates model output quality across hardware platforms, numerics, and serving configurations, and lead the investigation when it catches a regression\n Build the observability, dashboards, and modeling tools that make throughput, latency, cost, reliability, correctness, and their interactions legible across the stack\n Partner with kernel, serving, routing, autoscaling, and capacity teams to prioritize and land the highest-impact optimizations your analysis surfaces\n Ruthlessly stack-rank a large surface area of opportunities by impact and effort, and say no to the ones that don't make the cut\n \n Minimum Qualifications \n \n Hands-on performance engineering experience: profiling, roofline analysis, latency/throughput optimization, and root-cause investigation in complex production systems\n Proficiency in Python, with the ability to read, instrument, and contribute to large production codebases you didn’t write\n Solid data analysis skills (e.g. SQL, pandas, or similar) sufficient to turn raw telemetry into clear findings\n Ability to communicate quantitative results clearly in writing to influence priorities on teams you don't manage\n Genuine interest in correctness as an engineering discipline: numerics, evaluation design, regression detection\n \n Preferred Qualifications \n \n Experience with ML systems, especially training or inference infrastructure or general LLM serving stacks. Direct large-scale inference experience is a strong plus\n Familiarity with GPU/TPU/accelerator performance concepts (memory bandwidth, kernel overheads, quantization, collective communication). Reasoning about these matters more than having written kernels yourself\n Experience with reliability engineering for high-throughput services: autoscaling, load balancing, request routing, tail latency\n Experience with model evaluation or numerical regression-detection pipelines\n Experience building observability or telemetry for distributed systems\n Comfortable having impact through influence and evidence rather than direct ownership\n \n Representative Projects \n \n Trace a 350ms latency gap on a new accelerator platform from end-to-end request timing down to a server scheduling overhead, quantify the win, and land the fix directly or with the owning team\n Redesign the correctness eval gate: determine which signals reliably catch real model-output regressions versus noise, and make it the trusted release criterion across hardware backends\n Build a FLOPs funnel that breaks down where compute actually goes across the fleet, exposing the gap between achieved throughput and kernel rooflines\n Root-cause a numerical divergence between two hardware platforms to a specific kernel change, and define the acceptance threshold going forward\n Model the latency–cost impact of changing batch-sizing and utilization targets, and turn the result into the signal the autoscaler uses in production\n \n Deadline to apply: None. Applications ","salary_min":350000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"principal","tags":["distributed-systems","alignment","llm","research","inference"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5224564008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-20T22:53:11Z","expires_at":"2026-06-29T14:00:19.065435Z","created_at":"2026-05-27T14:00:24.711949Z","updated_at":"2026-05-30T14:00:19.17401Z","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/a62cc613-162e-4779-81ca-502537d39185"},{"id":"8068616e-2c82-4290-9a16-ebd2c6fcd45b","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Sr. Staff AI Research TLM - AI Systems","slug":"sr-staff-ai-research-tlm-ai-systems-9edbec07","description":"Principal Research Scientist – Scaling\n P-1227\n About Databricks AI\n At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development, by building and running the world’s best data and AI platform. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.\n About the Scaling Research Team\n The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low‑level implementation details with engineering partners.\n Role Summary\n As a Principal Research Scientist – Scaling, you will lead a team of world‑class researchers and engineers to advance the state of the art in large‑scale machine learning, focusing on post-training, RL and inference efficiency, optimization, and scaling. You will define and execute a research roadmap that advances the Databricks AI platform and delivers tangible improvements to how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders to bring cutting‑edge methods into production.\n The Impact You Will Have\n \n Lead and grow a multidisciplinary research team focused on foundational and applied AI problems, with a particular emphasis on LLM scaling, efficiency, and systems performance.\n Define the scaling research roadmap in alignment with Databricks’ strategic objectives, prioritizing advances in foundation model efficiency and large‑scale training and inference.\n Drive algorithmic innovations for large‑scale neural network training and inference, including novel optimizers, low‑precision techniques, and model adaptation methods, and guide your team in rigorous empirical validation against state‑of‑the‑art approaches.\n Optimize end‑to‑end ML systems for distributed training and RL, memory efficiency, and compute efficiency through close collaboration with core systems and platform teams, ensuring that research ideas translate into performant, reliable infrastructure.\n Partner with product and engineering to translate research breakthroughs, especially around scaling and efficiency, into customer‑impacting capabilities in the Databricks AI platform.\n Foster a culture of scientific excellence and openness, including high‑quality research practices, reproducible experimentation, and effective internal knowledge sharing across Databricks AI.\n Represent Databricks AI research externally through top‑tier publications, conference talks, and collaborations with academia and the open‑source community, with a focus on optimization and efficiency for large‑scale models.\n Mentor and develop talent, providing both technical guidance (research agendas, experimentation, implementation) and career development support for research scientists and engineers.\n \n What You Will Do\n \n Define and lead independent research programs on   foundation model efficiency, covering topics such as optimizer design, low‑precision training/inference, scalable model architectures, and efficient adaptation methods.\n Oversee the design and execution of large‑scale experiments, including benchmarking against state‑of‑the‑art methods and evaluating trade‑offs in quality, latency, throughput, and cost.\n Work hands‑on with your team on high‑quality, efficient code in Python and PyTorch for research implementation, rapid prototyping, and integration with Databricks’ production systems.\n Collaborate with distributed systems and infra teams to push the limits of distributed training ,  parallelism strategies, memory management, and hardware utilization for LLMs and other large models.\n Establish metrics, evaluation protocols, and best practices for scaling‑focused research (e.g., training efficiency, inference cost, energy usage) and drive their adoption across Databricks AI.\n Champion responsible and robust deployment of scaling innovations, ensuring that model behavior, reliability, and safety remain first‑class considerations.\n \n What We Look For\n \n Proven ability to lead a research team to develop novel techniques for foundation model efficiency and related topics, with a strong track record of industry impact. \n Deep expertise in at least one of: generative AI, LLMs, distributed ML systems, model optimization, or responsible AI, with a strong emphasis on scaling a","salary_min":270000,"salary_max":340000,"location":"Mountain View, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["generative-ai","distributed-systems","llm","agents","pytorch","deep-learning","data-pipeline","research"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8557780002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-20T09:40:26Z","expires_at":"2026-06-29T14:02:00.176089Z","created_at":"2026-05-27T14:02:12.463367Z","updated_at":"2026-05-30T14:02:00.284419Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8068616e-2c82-4290-9a16-ebd2c6fcd45b"},{"id":"657568b2-56d7-449f-a50d-936b9e173285","company_id":"aa372131-86ce-432a-af45-e2b42a79ba29","title":"Applied AI Researcher, Multi-Agent Systems","slug":"applied-ai-researcher-multi-agent-systems-4abe2461","description":"ABOUT DISTYL AI\n\nDistyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.\n\nWe research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.\n\nDistyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.\n\n\n\n\nWHAT WE ARE LOOKING FOR\n\nAt Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used.\n\nOur researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org.\n\n \n\n\nKEY RESPONSIBILITIES\n\n - The Multi-Agent Systems team focuses on designing architectures in which multiple agents coordinate to solve problems that require structured interaction across multiple reasoning processes. Researchers build systems that structure communication, route information, and coordinate decision-making across agents operating with different views of the problem\n\n - Researchers in Multi-Agent Systems investigate the interaction patterns that govern how agents collaborate. They study how agents exchange information, critique and refine each other’s reasoning, and coordinate execution across complex workflows. Their work identifies the mechanics behind effective communication, delegation, and coordination, in effect establishing the design language for how systems of agents can operate as cohesive, high-performing teams, with capabilities that arise from interaction rather than individual performance.\n\n \n\n\nWHAT WE REQUIRE\n\n - Built or studied systems where multiple agents collaborate through structured communication, delegation, critique, or iterative coordination.\n\n - Experience with agent orchestration, communication protocols, evaluator agents, or systems where multiple agents interact to exchange information, critique reasoning, and coordinate decisions over time\n\n - Experience with research in related fields, such as multi-agent reinforcement learning (MARL), graph neural networks (GNNs), knowledge graphs, mixed-initiative planning, etc.\n\n - Excited about making foundational advancements in how agents coordinate, reason and collaborate\n\n - Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done.\n\n - Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow.\n\n - Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI.\n\n - Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize.\n   \n    \n\n\nWHAT WE OFFER\n\n - The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package\n\n - 100% covered medical, dental, and vision for employees and dependents\n\n - 401(k) with additional perks (e.g., commuter benefits, in‑office lunch)\n\n - Access to state‑of‑the‑art models, generous usage of modern AI tools, and real‑world business problems\n\n - Ownership of high‑impact projects across top enterprises\n\n - A mission‑driven, fast‑moving culture that prizes curiosity, pragmatism, and excellence\n\nDistyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office.\n\n\n\n#LI-Hybrid\n\n\n\nWe believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all appl","salary_min":150000,"salary_max":250000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["deep-learning","healthcare","agents","reinforcement-learning","research"],"apply_url":"https://jobs.ashbyhq.com/distyl/1a44c296-a732-4374-9f8c-a613b17ae37b/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T22:41:22.889Z","expires_at":"2026-06-29T14:17:46.927997Z","created_at":"2026-05-27T14:18:38.728992Z","updated_at":"2026-05-30T14:17:47.047265Z","company_name":"Distyl AI","company_slug":"distyl-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=distyl.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/657568b2-56d7-449f-a50d-936b9e173285"},{"id":"cdb4264b-9975-4524-b6bd-3c0e216f6177","company_id":"a0000000-0000-0000-0000-000000000003","title":"Research Scientist, Safety Post Training","slug":"research-scientist-safety-post-training-c518e4c9","description":"Scale Labs, Research Scientist — Safety Post Training \n As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities.\n Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision.\n As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: \n \n Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties;\n Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations;\n Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices.\n \n  \n Ideally you’d have: \n \n Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance.\n Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches.\n A track record of published research in machine learning, particularly in generative AI.\n At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development.\n Strong written and verbal communication skills to operate in a cross-functional team.\n \n Nice to have: \n \n Experience with mechanistic interpretability, probing, or other techniques for understanding model internals.\n Familiarity with red-teaming or adversarial evaluation of post-trained models.\n Experience studying failure modes introduced or masked by post-training, such as reward hacking, sycophancy, or alignment faking.\n \n Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement.\n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:\n $216,000 — $270,000 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army a","salary_min":216000,"salary_max":270000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["alignment","reinforcement-learning","generative-ai","research"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4696595005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T19:54:26Z","expires_at":"2026-06-29T14:01:12.598488Z","created_at":"2026-05-19T14:01:22.953727Z","updated_at":"2026-05-30T14:01:12.708729Z","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/cdb4264b-9975-4524-b6bd-3c0e216f6177"}],"page":1,"per_page":20,"total":760,"total_pages":38}