{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","employer_pilot_url":"https://aidevboard.com/verified-interview-pilot","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"candidate_resume_action":{"application_authorized":false,"candidate_charge":0,"endpoint":"https://aidevboard.com/api/v1/candidate/resume-preview","job_id_json_path":"jobs[].id","method":"POST","preview_requires_identity":false,"required_body_fields":["job_id","evidence_bullets"],"requires_explicit_human_review":true,"saved_artifact_protocol":"mcp","saved_artifact_requires_verified_human":true,"saved_artifact_tool":"compile_job_specific_resume","search_requires_identity":false,"status":"available_after_candidate_selects_job","submission_performed":false,"uses_candidate_verified_evidence":true},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"6e489569-b334-49ce-8208-039de04ea5ce","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Research Scientist, RL for Autonomous Planning \u0026 World Modeling  ","slug":"research-scientist-rl-for-autonomous-planning-world-modeling-adc21b92","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. \n In this hybrid role, you will report to a Principal Scientist.\n You will: \n \n Participate in Waymo’s Foundation World Model post-training and evaluation\n Research and develop cutting edge RL and Distillation techniques for Autonomous Vehicle Trajectory Planning\n Integrate emerging research from the broader AI community into Waymo’s internal RL infrastructure, conducting rigorous ablations to identify and scale the most promising methods\n Partner with engineering and research teams across Waymo to share recipes, techniques, and post-training best practices to accelerate our collective know-how\n \n You have: \n \n PhD or Masters in Computer Science, Machine Learning, Robotics, or a similar technical field; with 3+ years of industry or post-doc research experience in Reinforcement Learning or Foundation Models\n Demonstration of original contributions to the field through high-impact publications (ArXiv, peer-reviewed conferences like NeurIPS/ICLR/CVPR), technical blog posts, or significant open-source contributions\n Proficiency in implementing model training flows in a scalable, distributed and performant manner such as Data parallel, FSDP and other sharding approaches\n A willingness to work with complexity of globally distributed inference infrastructure\n \n We prefer: \n \n PhD in Computer Science, Machine Learning, or Robotics, with a research focus on Reinforcement Learning, Foundation Models, or Multi-Modal learning\n Extensive experience designing and deploying Reinforcement Learning infrastructure, specifically for on-policy learning or alignment with human preferences\n A consistent history of original contributions to the AI community, evidenced by first-author publications at top-tier venues (e.g., NeurIPS, ICLR, ICRA) or maintaining significant open-source ML projects\n Experience with large scale (many-machine) training infrastructure and techniques for inference with large models such as model sharding/tensor-parallel\n \n In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:\n \n Health, dental, vision, life, disability insurance\n Retirement Benefits: 401(k) with company match\n Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment\n Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)\n Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks\n Baby Bonding Leave: 18 weeks\n Holidays: 13 paid days per year\n \n Please note that Waymo may not be able to employ remotely in all locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process\n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $204,000 — $259,000 USD","salary_min":204000,"salary_max":259000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","robotics","autonomous-vehicles","reinforcement-learning","research"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8165872","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-30T02:06:16Z","expires_at":"2026-09-30T13:35:11.000977Z","created_at":"2026-08-30T13:35:05.638136Z","updated_at":"2026-08-31T13:35:11.12245Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6e489569-b334-49ce-8208-039de04ea5ce"},{"id":"e1618a18-e64a-423b-82d5-022f365f7715","company_id":"df455adb-5b5f-43b9-a3bf-eb48405d2b7b","title":"Software Engineer, Applied AI Research","slug":"software-engineer-applied-ai-research-229b4f6a","description":"About Hightouch\n Hightouch is an Agentic Marketing Platform powered by the industry-leading Composable CDP. With complete brand context, customer data, and performance history in one place, every marketer finally has the power to build and ship end-to-end campaigns themselves. Teams move faster, stay on brand, and get AI marketing that actually works.\n Founded in 2019 and headquartered in San Francisco, Hightouch enables marketing teams to analyze performance, brainstorm ideas, and generate creative at a speed and quality that wasn't previously possible.\n Named a Leader in the 2026 Gartner® Magic Quadrant™ for Customer Data Platforms, Hightouch is trusted by leading enterprises like Domino's, Spotify, Aritzia, Cars.com, Ramp, and PetSmart.\n At Hightouch, our mission is to help our customers leverage data and AI to grow their businesses. The team is ambitious, impact-driven, efficient — and we believe humility, kindness, and compassion are essential to our success. If you're energized by velocity, obsessed with raising the bar, and want to build alongside people who care deeply about each other and our customers, we'd love to meet you.\n About the Role \n We’re looking to add  applied AI research engineers  to the team. The ideal candidate will have strong probabilistic and quantitative thinking, the ability to be highly creative and experimental with LLM applications, and ground their work in potential customer and product applications.\n Our applied research team focuses on finding new and innovative techniques to improve the frontier of what is possible in agentic AI marketing applications, with a particular focus on image and video. We focus less on theory or writing research papers, and more on experimenting, prototyping, and exploring new methods for applying generative AI to help our customers grow their companies.\n Example workstreams include:\n \n Quickly iterating and developing proofs of concept (POCs) to explore the maximum potential of integrating AI into data and marketing workflows\n Design and develop evaluation and improvement systems that can make advancements autonomously\n Expanding the frontier of what is feasible with AI generated video (e.g. making generated humans maximally realistic)\n Experiment with different approaches for generating brand assets that stay aligned to a particular company’s look and feel\n \n We're seeking talented, intellectually curious, and motivated individuals interested in exploring the forefront of AI. While no prior experience with LLMs and AI is required, strong technical skills, particularly in backend architecture or probabilistic systems, and product intuition are essential for understanding and executing these projects from start to finish.\n This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000 - $400,000 USD per year, which is location independent in accordance with our remote-first policy.\n Interview Process\n Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense and creativity with LLMs, ability to architect backend systems, and alignment with Hightouch’s values. Notably, we don’t do any programming interviews as we believe they are low signal to noise and aren’t a good evaluation mechanism.\n \n Recruiter Screen [30m]:  Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit.\n System Design Screen [60m]:  Designing a data processing or machine learning feature end-to-end (depending on background).\n Hiring Manager Interview [30m]:  Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.\n Agent Building Systems Interview [75m]:  Work with the interviewer to architect an agentic system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.\n \n \n E-Verify Statement \n Hightouch participates in E-Verify. After you join the team, we'll verify your eligibility to work in the U.S. by submitting information from your Form I-9 to the Social Security Administration and, if needed, the Department of Homeland Security. This process happens post-hire only — we never use E-Verify to pre-screen applicants. \n E-Verify Notice E-Verify Notice (Spanish) Right to Work Notice Right to Work Notice (Spanish)","salary_min":180000,"salary_max":400000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["llm","search","agents","generative-ai","research"],"apply_url":"https://job-boards.greenhouse.io/hightouch/jobs/6174215004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T21:18:55Z","expires_at":"2026-09-30T13:38:23.460196Z","created_at":"2026-08-29T13:38:40.813703Z","updated_at":"2026-08-31T13:38:23.591408Z","company_name":"Hightouch","company_slug":"hightouch","company_logo_url":"https://www.google.com/s2/favicons?domain=hightouch.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e1618a18-e64a-423b-82d5-022f365f7715"},{"id":"c0509020-b00e-47f4-9cd5-7680b67c5c2f","company_id":"219030bb-3e37-4376-be76-0ea3c447e4b2","title":"Research Quality Analyst","slug":"research-quality-analyst-97f71c69","description":"About AlphaSense:  \n The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. \n The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S\u0026P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! \n About Expert Insights: \n Expert Insights, which spans AlphaSense’s Expert Transcript Library and 1x1 Call Services offerings,  delivers a new and transformative form of market intelligence content. Through transcripts covering thousands of companies, it captures the unfiltered views and insights of business operators in the trenches, interviewed by professional investors who drill into key questions on what’s truly important about a company at each moment in time. AlphaSense’s library of over 220,000 transcripts is the market’s largest, covering all sectors of the economy, with thousands more published each month. Expert Insights is quickly becoming a table-stakes solution for institutional investors to choose the right companies to invest in while gaining rapid adoption among all other consumers of market intelligence from sell-side research and banking, consultancies, and large corporations.\n About the Team: \n The Directed Content Team is an integral part of the Expert Insights group, generating thousands of calls each quarter on high-value, strategic content targets — ensuring that the AlphaSense Expert Transcript Library (ETL) delivers comprehensive coverage to our users. The Directed Content team is responsible for identifying, recruiting, and onboarding the best possible experts from around the world based on the targets and topics we are looking to generate content against — ensuring that the interviews with those experts are of the highest possible quality and relevance.\n About the Role:  \n As the Research Quality Analyst on the Directed Content (DC) team, you will provide quality control across a continuous, high-volume research pipeline. This role uses sampling across the project lifecycle to catch quality issues, identify patterns, and drive improvements to process and AI prompting that raise the overall quality and consistency of DC's research output. You will be a key player in ensuring that our research is accurate, consistent, and valuable to our clients. This position offers an opportunity to develop expertise in AI-powered research and to contribute to refining workflows that generate trackable, high-quality insights.\n What You’ll Do:  \n \n Sample and review research projects at multiple stages — prompt sheets, knowledge bases, and published expert transcripts — to catch quality issues both before and after publication.\n Identify patterns in quality driven by process gaps or issues.\n Test and help deploy process and prompt fixes that address those patterns, so quality review becomes faster and narrower in scope over time.\n Assist in refining and iterating on AI prompts.\n Help develop and maintain QA checklists and documentation, standardizing quality practices.\n Track and analyze quality metrics, reporting on trends, and recommending process improvements.\n Support testing of new AI-driven tools and workflows as they're introduced to Directed Content.\n \n Who You Are: \n \n You have 1–3 years of experience in a role focused on quality assurance, content review, copy editing, research, or data analysis.\n You possess an exceptional eye for detail and a commitment to producing high-quality work.\n You are highly analytical and intellectually curious, with the ability to quickly understand new concepts and identify inconsistencies in data and text.\n You have excellent written and verbal communication skills, with experience editing and proofreading professional documents.\n You are comfortable working collaboratively in a fast-paced, cross-functional environment.\n You have a strong interest in technology and artificial intelligence; experience with AI or large language models is a significant plus.\n For base compensation, we set standard ranges for all roles based on function and level benchmarked against similar stage growth companies and internal comparables. In ","salary_min":62000,"salary_max":77000,"location":"Chicago, IL","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["data-pipeline","payments","search","llm","research"],"apply_url":"https://job-boards.greenhouse.io/alphasense/jobs/8692344002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T20:38:01Z","expires_at":"2026-09-30T13:41:24.023968Z","created_at":"2026-08-29T13:41:39.658903Z","updated_at":"2026-08-31T13:41:24.144195Z","company_name":"AlphaSense","company_slug":"alphasense","company_logo_url":"https://www.google.com/s2/favicons?domain=alpha-sense.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c0509020-b00e-47f4-9cd5-7680b67c5c2f"},{"id":"1cab6a2a-2b5f-4e26-b0dd-0a2b833905b0","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, RL Data Platform","slug":"staff-software-engineer-rl-data-platform-224ae32b","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 RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from: the interfaces humans use to give feedback, the pipelines that turn raw feedback into training signal, and the tooling researchers use to launch, monitor, and inspect data collection. Every RL run depends on a steady supply of high-quality data - human feedback, expert demonstrations, graded transcripts - and when a researcher has an idea for new data on Monday, our job is to make it collectable by Wednesday and in the training mix by Friday.\n This is a full-stack, ownership-heavy role on a small, senior team. You'll design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why. You'll scope your own projects, make architectural calls, and see them through to production. We're looking for engineers who treat researchers as their users, build for reliability first, and care as much about the shape of the data leaving the system as the UI going into it.\n Key responsibilities \n \n \n Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers.\n \n Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training.\n \n Own the reliability, latency, and usability of systems that run continuously against live model endpoints.\n \n Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and the tooling to run them.\n \n Build dashboards, monitoring, and inspection tools so researchers can see data quality and throughput without asking an engineer.\n \n Identify and remove the bottlenecks between \"we want this data\" and \"it's in the training mix\".\n \n Minimum qualifications \n \n \n Strong full-stack engineering skills, with production experience in TypeScript/React on the frontend and Python on the backend.\n \n Experience designing and operating backend services and data pipelines that other teams depend on.\n \n A track record of owning projects end-to-end, from an ambiguous brief to something in production that people use.\n \n Comfort working directly with technical stakeholders whose needs change week to week, and the judgment to push back when something isn't worth building.\n \n Effective use of AI tools in your own day-to-day work.\n \n Care about the societal impacts of your work.\n \n Preferred qualifications \n \n \n Experience building annotation, labelling, evaluation, or other human-in-the-loop data tooling.\n \n Experience with RLHF, preference data, or other human-feedback pipelines for ML systems.\n \n Experience shipping researcher-facing or other expert-facing internal tools people love: interviewing users, hunting down friction, measurably improving the experience.\n \n Experience running experiments on data collection interfaces and using the results to improve data quality.\n \n Experience working with crowdworker or expert vendor platforms at scale.\n \n Familiarity with how LLMs are trained and evaluated.\n \n Representative projects \n \n \n Build an interface that lets a domain expert review a long agentic transcript, flag the step where things went wrong, and write a corrected continuation - with the result landing in a training-ready format.\n \n Rework the sampling path between our feedback interfaces and model endpoints to cut time-to-first-sample for annotators.\n \n Build a campaign launcher that lets a researcher stand up a new data collection effort (task, rubric, population, quality checks) without writing code.\n \n Instrument annotator behaviour to detect low-effort or adversarial work and surface it to the quality team automatically.\n \n Design the data model for a kind of feedback we haven't collected before, and ship the pipeline that gets it into the training mix.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $405,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","alignment","agents","llm","data-pipeline","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5404730008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T13:21:33Z","expires_at":"2026-09-30T13:30:44.268315Z","created_at":"2026-08-27T13:30:43.573151Z","updated_at":"2026-08-31T13:30:44.390163Z","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/1cab6a2a-2b5f-4e26-b0dd-0a2b833905b0"},{"id":"d9e245d1-a6c7-4071-9742-6a6ed60d8557","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Research Engineer, RL Data Platform","slug":"staff-research-engineer-rl-data-platform-41e9b926","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 RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from: the interfaces humans use to give feedback, the pipelines that turn raw feedback into training signal, and the tooling researchers use to launch, monitor, and inspect data collection. Every RL run depends on a steady supply of high-quality data - human feedback, expert demonstrations, graded transcripts - and when a researcher has an idea for new data on Monday, our job is to make it collectable by Wednesday and in the training mix by Friday.\n This is a full-stack, ownership-heavy role on a small, senior team. You'll design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why. You'll scope your own projects, make architectural calls, and see them through to production. We're looking for engineers who treat researchers as their users, build for reliability first, and care as much about the shape of the data leaving the system as the UI going into it.\n Key responsibilities \n \n \n Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers.\n \n Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training.\n \n Own the reliability, latency, and usability of systems that run continuously against live model endpoints.\n \n Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and the tooling to run them.\n \n Build dashboards, monitoring, and inspection tools so researchers can see data quality and throughput without asking an engineer.\n \n Identify and remove the bottlenecks between \"we want this data\" and \"it's in the training mix\".\n \n Minimum qualifications \n \n \n Strong full-stack engineering skills, with production experience in TypeScript/React on the frontend and Python on the backend.\n \n Experience designing and operating backend services and data pipelines that other teams depend on.\n \n A track record of owning projects end-to-end, from an ambiguous brief to something in production that people use.\n \n Comfort working directly with technical stakeholders whose needs change week to week, and the judgment to push back when something isn't worth building.\n \n Effective use of AI tools in your own day-to-day work.\n \n Care about the societal impacts of your work.\n \n Preferred qualifications \n \n \n Experience building annotation, labelling, evaluation, or other human-in-the-loop data tooling.\n \n Experience with RLHF, preference data, or other human-feedback pipelines for ML systems.\n \n Experience shipping researcher-facing or other expert-facing internal tools people love: interviewing users, hunting down friction, measurably improving the experience.\n \n Experience running experiments on data collection interfaces and using the results to improve data quality.\n \n Experience working with crowdworker or expert vendor platforms at scale.\n \n Familiarity with how LLMs are trained and evaluated.\n \n Representative projects \n \n \n Build an interface that lets a domain expert review a long agentic transcript, flag the step where things went wrong, and write a corrected continuation - with the result landing in a training-ready format.\n \n Rework the sampling path between our feedback interfaces and model endpoints to cut time-to-first-sample for annotators.\n \n Build a campaign launcher that lets a researcher stand up a new data collection effort (task, rubric, population, quality checks) without writing code.\n \n Instrument annotator behaviour to detect low-effort or adversarial work and surface it to the quality team automatically.\n \n Design the data model for a kind of feedback we haven't collected before, and ship the pipeline that gets it into the training mix.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $500,000 — $850,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job","salary_min":500000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["alignment","llm","reinforcement-learning","agents","search","data-pipeline","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5404725008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T13:04:41Z","expires_at":"2026-09-30T13:30:38.443577Z","created_at":"2026-08-27T13:30:36.814345Z","updated_at":"2026-08-31T13:30:38.564222Z","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/d9e245d1-a6c7-4071-9742-6a6ed60d8557"},{"id":"a60887bd-18b6-4819-b8ac-a8ce688f7d3f","company_id":"a0000000-0000-0000-0000-000000000003","title":"Machine Learning Research Scientist, Evaluations","slug":"machine-learning-research-scientist-evaluations-47ca5c35","description":"Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities.\n In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models.\n You will: \n \n Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents.  You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA.\n Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities.\n Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them.\n Publish research findings in top-tier AI conferences.\n \n Ideally you’d have: \n \n Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.\n Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.\n Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development.\n Excellent written and verbal communication skills.\n Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals.\n Previous experience in a customer facing role.\n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:\n $180,600 — $225,750 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. \n We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  \n We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. \n We comply with the United States Department of Labor's Pay Transparency provision .  \n PLEASE NOTE: We co","salary_min":180600,"salary_max":225750,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["search","fine-tuning","nlp","llm","deep-learning","reinforcement-learning","generative-ai","research"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4728014005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T18:51:42Z","expires_at":"2026-09-30T13:31:41.024693Z","created_at":"2026-08-27T13:31:38.7307Z","updated_at":"2026-08-31T13:31:41.149391Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a60887bd-18b6-4819-b8ac-a8ce688f7d3f"},{"id":"9a42e317-7954-4330-9e7d-59cad3214bb9","company_id":"8115806a-6d9c-48b9-9a92-5eb180bbd1ef","title":"Applied Research Scientist, AI Research","slug":"applied-research-scientist-ai-research-428d0a90","description":"Descript's Research team builds the models behind the product's most distinctive features: Video Regenerate and lipsync, video translation, zero-shot voice and roomtone cloning, and Studio Sound. We don't build general-purpose generative models. We pick specific problems in the editing workflow and build specialized models for them. This isn't research for its own sake. Everything we build is meant to ship, and most of it has, going from prototype to a production feature used by millions of creators within months.\n This role is focused on multimodal understanding: training models to perceive edited media the way a human video editor does. Underlord, our AI editing agent, reasons about a project largely through a textual representation of it. Giving it direct perception of the media it's working on is what will let it judge its own output and reason about the creative choices in an edit, not just the structure of a project. It's also an open research problem, since there's no settled way to represent or evaluate editorial craft, whether a cut lands or whether the pacing works. We have a unique dataset to work with.\n Some recent work from the team:\n \n Audio editing by latent inpainting : regenerating a masked span of speech \n Video Regenerate : regenerating a speaker's lower face to match new or translated audio\n Jumpcut Smoothing : generating a bridge across a cut so the join plays like a continuous take\n Anchored Tree Sampling : tree-based imputation that bounds drift in long video generation\n PoDAR : disentangling power from semantics in audio latents to make them easier to model\n \n More at descript.com/research .\n What you'll do\n \n Multimodal understanding: build vision-language systems that let Descript's agentic editing features reason over the visual and audio content of a project.\n Evaluation: design the benchmarks and evals that make editorial quality measurable, and that balance quality against cost and latency.\n Data: build the datasets your work depends on, including synthetic data generation where real examples don't exist at scale.\n Training: train specialized models from scratch or fine-tune existing foundation models, whichever gets the capability we need.\n Shipping: take models from prototype to production with the agent and engineering teams.\n Direction-setting: identify the next research direction that should become a Descript feature, not just a paper. More senior candidates should expect to own this directly; more junior candidates will grow into it.\n Publishing: take your work to academic venues if you'd like. We support it, but it isn't a requirement of the role.\n \n What you bring\n Required\n \n Proven ability to design and implement deep learning algorithms, demonstrated by publications, open-source work, or models you've shipped.\n Strong programming skills and deep fluency in PyTorch.\n A track record of generating new ideas in machine learning. You produce more ideas than you can implement, and once an experiment setup is established, you can run and evaluate many of them quickly rather than being bottlenecked on infrastructure.\n Strong experimental judgment. You test ideas fast, and you're honest with yourself and the team about which ones don't pan out.\n Clear written and verbal communication, including when a direction isn't working, so the team doesn't waste time following a lead that's already dead.\n A PhD or Master's in deep learning or a related field, or equivalent experience. We care about the track record more than the credential.\n \n At least one of the following must be true:\n \n Lead or first author of an accepted publication in a top venue: CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, or similar.\n Played a key role in shipping a production feature with deep learning as a core component.\n \n More senior candidates (Senior and Staff) should also bring a track record of owning research direction rather than executing a plan handed to them, and experience mentoring or technically leading other researchers or engineers.\n Where breadth helps\n Direct experience in multimodal understanding is welcome but not required, and we don't require domain-specific expertise in computer vision or speech and audio. Our team spans both, and strong general deep learning ability transfers. We hire against the bar above, and then expect you to grow into the domain. Depth in any of these is a strong signal:\n \n Vision-language models and multimodal understanding.\n Generative modeling for video, audio, or images.\n Post-training, fine-tuning, and RL on large foundation models.\n Building evaluation systems for generative or agentic outputs where metrics resist clean definitions.\n Taking a research idea through to a shipped, production-facing feature.\n \n Compensation and benefits\n Base salary range: $197,000–$262,500, plus equity and benefits. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, and level, and may vary from the amount above.\n  \n IMPO","salary_min":197000,"salary_max":262500,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","generative-ai","healthcare","deep-learning","fine-tuning","pytorch","computer-vision","research"],"apply_url":"https://boards.greenhouse.io/descript/jobs/7967440003?gh_jid=7967440003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T00:18:24Z","expires_at":"2026-09-30T13:36:02.375737Z","created_at":"2026-08-25T18:27:44.358668Z","updated_at":"2026-08-31T13:36:02.495917Z","company_name":"Descript","company_slug":"descript","company_logo_url":"https://www.google.com/s2/favicons?domain=descript.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9a42e317-7954-4330-9e7d-59cad3214bb9"},{"id":"30922887-a8eb-4d71-b922-a837aef04ace","company_id":"4c0fefc3-173a-4227-a823-4d67d3e70ff0","title":"Senior Research Engineer","slug":"senior-research-engineer-9f57f845","description":"Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.\n Our base salary range is $174,240 - $261,360, and in addition we have generous bonus plans to provide a competitive compensation package. \n Who You Are: \n OlmoEarth is growing — more partners, more use cases, and a platform that is evolving quickly. We are looking for a Senior Research Engineer who can collaborate with our partners to tailor the OlmoEarth models to a wide range of specific applications across multiple domains. \n Who We Are:  \n OlmoEarth is an open, end-to-end platform built around a family of foundation models for Earth observation. The platform enables users to create custom fine-tuned models to detect and classify novel geospatial features, handling the full loop: imagery acquisition, annotation, distributed model training and inference, and visualization.\n Our partners span some of the most respected institutions working on wildfire risk, crop mapping, mangrove conservation, and forest protection. OlmoEarth sits within the AI for the Planet group at the Allen Institute for AI, a small, mission-driven team working on conservation, food security, disaster resilience, and climate solutions.\n Learn more: https://allenai.org/olmoearth \n What We Believe \n \n The mission is the point. OlmoEarth exists to put powerful Earth observation tools into the hands of people working on conservation, food security, and climate. Every partner engagement this role supports is connected to that goal. If it matters to you that your day-to-day work adds up to something larger, you are in the right place.\n Good operations are invisible and indispensable. When coordination, documentation, and follow-through are working well, the whole team moves faster and partners have a better experience. This role is the engine behind that.\n Our partners are the signal. We learn what to build and how to improve by staying close to the people using the platform. The feedback, patterns, and friction you surface in this role directly shapes what the team works on next.\n In-person matters. A lot of the best work on this team happens in quick, unplanned conversations between engineering, research, and partnerships. We are mostly in the office because that is where this kind of collaboration happens naturally.\n Say what you think. We make better decisions when people share what they are actually seeing — whether that is a process that is not working, a partner need we are missing, or an idea for doing something differently. Everyone here is still learning, and we like it that way.\n \n Your Next Challenge: \n You will work with partners to deploy OlmoEarth for their use cases. This will require you to move fluidly across the entire OlmoEarth team, working with partners, engineers and researchers. You will make meaningful contributions to all the components of OlmoEarth’s infrastructure (from the finetuning code to model pretraining to our rslearn backend).\n Use case enablement \n \n Collaborate closely with partners to deploy OlmoEarth models in challenging contexts. This will prioritize contexts and partners for which we don’t have immediate solutions or there’s an opportunity to standardize a high quality approach for common use cases.. \n Explore novel use cases for the OlmoEarth models (e.g. post-hoc addition of new modalities, effectively leveraging embeddings in different contexts) which can unlock new use cases and partners.\n \n Partner Communications \u0026 Coordination \n \n As part of model development, maintain communications with key partners to ensure their success using the OlmoEarth platform.\n Communicate  internally  so that partner needs are clearly understood by the OlmoEarth machine learning research, engineering and partnership teams. \n \n Product Improvement and Research \n \n Work closely with the engineering and partnerships  team to feed lessons you learn when deploying models into our infrastructure. This includes improvements to rslearn, OlmoEarth Studio. \n Collaborate with the research team to identify and fix issues with the OlmoEarth models preventing their deployment in specific important applications. \n Continually update our model adaptation approaches to improve model performance for all our partners. This includes updating our fine-tuning approaches, developing recipes for new applications and improving the UI so that modelling trade-offs can be better understood by users. \n Support agent evaluations and development.\n \n What You’ll Need: \n Required\n \n 2+ years of experience deploying machine learning solutions. This covers the full stack of machine learning, including understanding the business case and requirements, training models, and deploying them at scale.\n Technical experience using machine learning tools. This includes fluency in PyTorch, experience debugging traini","salary_min":174240,"salary_max":261360,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["robotics","pre-training","generative-ai","pytorch","search","fine-tuning","research"],"apply_url":"https://job-boards.greenhouse.io/thealleninstitute/jobs/8140098","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T18:47:01Z","expires_at":"2026-09-30T13:48:27.755812Z","created_at":"2026-08-25T18:32:53.66843Z","updated_at":"2026-08-31T13:48:27.871069Z","company_name":"Allen Institute for AI","company_slug":"allen-institute-for-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=allenai.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/30922887-a8eb-4d71-b922-a837aef04ace"},{"id":"e83f9b8b-565f-4a94-b2f4-03b79a6f7843","company_id":"2114efab-ea67-411b-bfb8-7899153105f3","title":"Member of Technical Staff, Site Reliability Engineer","slug":"member-of-technical-staff-site-reliability-engineer-369fc8ef","description":"Overview\n\nInferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.\n\nAbout the Role\n\nWe're looking for a Site Reliability Engineer to help make vLLM-powered inference systems reliable, observable, and operationally simple at production scale. This role is for someone who thinks about failure before launch, designs systems that are easier to operate, and knows how to turn incidents into durable improvements rather than one-off fixes.\n\nYou'll work across engineering and infrastructure to define SLOs, improve monitoring and alerting, strengthen incident response, drive post-mortems, and reduce operational risk before it reaches users. Your work will directly impact the reliability, availability, and production readiness of the systems powering AI inference at scale.\n\n\n\nSkills and Qualifications\n\nMinimum qualifications:\n\n - Bachelor's degree or equivalent experience in computer science, engineering, systems, infrastructure, or similar.\n\n - Strong experience operating production systems with meaningful traffic, user impact, or infrastructure criticality.\n\n - Deep understanding of SLOs, SLIs, error budgets, alerting, incident response, and post-mortem processes.\n\n - Experience live-fighting major production incidents, including mitigation, root cause analysis, escalation, and follow-through on prevention work.\n\n - Strong Linux, networking, systems debugging, observability, and distributed systems fundamentals.\n\n - Ability to design operationally simple systems and identify likely failure modes before launch.\n\n - Strong programming or scripting ability in Python, Go, Bash, or similar for automation, tooling, and reliability improvements.\n\nPreferred qualifications:\n\n - Experience supporting ML infrastructure, inference systems, GPU workloads, Kubernetes-based platforms, or high-scale backend services.\n\n - Experience building or improving observability systems using metrics, logs, traces, dashboards, alerts, and runbooks.\n\n - Experience with Kubernetes, Docker, Terraform, cloud infrastructure, service meshes, CI/CD systems, or production deployment platforms.\n\n - Experience driving incident review culture, post-mortem processes, reliability reviews, and prevention-oriented engineering work.\n\n - Ability to partner with engineering teams to improve service design, release safety, capacity planning, and operational readiness.\n\nBonus points if you have:\n\n - Owned reliability for high-throughput, latency-sensitive, or mission-critical production systems.\n\n - Supported AI inference, model serving, GPU clusters, ML platforms, or distributed serving infrastructure.\n\n - Built automation that reduced toil, improved recovery time, or prevented repeat incidents.\n\n - Led incident response for severe outages with clear communication across engineering and leadership.\n\n - Created practical SLOs, dashboards, alerts, runbooks, or release gates that improved production reliability.\n\n\n\nLogistics\n\n - Location: This role is based in San Francisco, California. Will consider remote in the US for exceptional candidates.\n\n - Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.\n\n - Visa sponsorship: We sponsor visas on a case-by-case basis.\n\n - Benefits: We offers generous health, dental, and vision benefits as well as 401(k) company match.","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","llm","gpu","mlops","distributed-systems","devops","research"],"apply_url":"https://jobs.ashbyhq.com/inferact/ad992ead-2a9a-4694-8fca-0504354548cd/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T18:25:22.552Z","expires_at":"2026-09-30T13:41:59.818121Z","created_at":"2026-08-25T18:30:22.617589Z","updated_at":"2026-08-31T13:41:59.94608Z","company_name":"Inferact","company_slug":"inferact","company_logo_url":"https://www.google.com/s2/favicons?domain=inferact.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e83f9b8b-565f-4a94-b2f4-03b79a6f7843"},{"id":"d5aae1c9-cae9-47d5-9fce-478d44a8cb20","company_id":"4ed3e523-b627-46ed-8dae-04c2ea823be2","title":"Research Scientist/Research Engineer, Reinforcement Learning ","slug":"research-scientistresearch-engineer-reinforcement-learning-2476fcd9","description":"Jump Trading Group is committed to world-class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting-edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk-adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.\n Our team is a group of quantitative researchers, engineers, and ML experts leading reinforcement learning research and trading at Jump. Our mission is to combine emerging techniques and original research to learn optimal decision-making policies from financial market data and monetize them globally. We are building the future of ML-powered trading through breakthrough reinforcement learning, and we're looking for an exceptional Research Scientist/Research Engineer to join our team.\n What You’ll Do \n As a Research Scientist/Research Engineer working on RL, you'll be at the forefront of applying reinforcement learning to markets. You'll conduct original research and own the systems that turn it into production trading: designing and evaluating policy architectures, reward formulations, and objective horizons with rigorous out-of-sample benchmarking; partnering with trading and research teams to source, integrate, and validate their alpha signals within the RL framework; ensuring simulation fidelity against live trading by modeling market microstructure, fill dynamics, liquidity, and latency; building efficient tooling to store, process, and analyze very large volumes of market and signal data; and communicating findings to technical and trading audiences. This isn't incremental optimization; we're pushing the boundaries of what reinforcement learning can do at scale, where your improvements directly impact live trading.\n Other duties as assigned or needed. Skills You’ll Need \n \n 5+ years of experience developing reinforcement learning and/or deep learning systems with measurable impact in industry and/or academia\n Depth in reinforcement learning, including experience designing reward formulations, policy architectures, and evaluation, and taking RL methods from research into production\n Proficiency in Python and/or C++\n Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX\n Strong foundation in mathematics and statistics\n PhD or Master's degree in Computer Science, Machine Learning, Robotics (or a related subject)\n Strong publication record at ICML, ICLR, AAAI, NeurIPS, CVPR, or equivalent\n Ability to thrive in a collaborative, team-oriented environment\n Creative thinkers who are driven, self-motivated, and eager to solve challenging problems\n Reliable and predictable availability\n Excellent written and verbal communication skills in English\n Benefits \n \n Discretionary bonus eligibility \n Medical, dental, and vision insurance \n HSA, FSA, and Dependent Care options \n Employer Paid Group Term Life and AD\u0026D Insurance \n Voluntary Life \u0026 AD\u0026D insurance \n Paid vacation plus paid holidays \n Retirement plan with employer match \n Paid parental leave \n Wellness Programs \n \n Annual Base Salary Range \n $200,000 — $350,000 USD","salary_min":200000,"salary_max":350000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["search","tensorflow","robotics","deep-learning","reinforcement-learning","pytorch","research"],"apply_url":"https://www.jumptrading.com/hr/job?gh_jid=8122860","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-18T18:54:10Z","expires_at":"2026-09-30T13:48:42.613981Z","created_at":"2026-08-27T13:48:12.175153Z","updated_at":"2026-08-31T13:48:42.720164Z","company_name":"Jump Trading","company_slug":"jump-trading","company_logo_url":"https://www.google.com/s2/favicons?domain=jumptrading.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d5aae1c9-cae9-47d5-9fce-478d44a8cb20"},{"id":"3c301340-19ad-4a31-8d61-d1c8287d1477","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Staff UX Researcher - AI Agents","slug":"staff-ux-researcher-ai-agents-9f88df43","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n You will proactively construct and own an AI-forward research roadmap for key product pillars at Okta, operating at the intersection of Identity, Security, and Artificial Intelligence. As a Staff-level individual contributor, you will drive both qualitative and quantitative methodologies to define user experiences for non-deterministic AI agents, automated workflows, and developer platforms. Additionally, you leverage agentic tools and AI workflows internally to scale qualitative coding, synthesis, and research operations across the organization.\n In this role, you’ll get to:\n \n Drive AI Agent Research: Lead foundational and evaluative research on autonomous AI agents and the security thereof.\n Execute Balanced Mixed-Methods: Drive qualitative depth (contextual inquiry, cognitive walkthroughs) and quantitative rigor (large-scale surveys, behavioral telemetry, statistical modeling) to evaluate AI products.\n Pioneer AI Research Operations: Integrate AI tools, prompt engineering, and agentic research workflows into your daily practice to accelerate quality research outputs.\n Lead Cross-Discipline Collaboration: Facilitate research to drive cross-discipline clarity, executive alignment, and decision-making across complex security and admin workflows.\n Solve Complex Problems: Bring stakeholders together across multiple teams to scope problems and collaborate on research in ways that nurture a culture of curiosity and learning.\n Cultivate Empathy: Design mechanisms to build up customer empathy and deep knowledge of our partners, end users, consumers, administrators, and other identified audiences.\n Tell High-Impact Stories: Represent your research to diverse audiences across the organization by telling compelling stories that motivate others to solve complex needs with your insights.\n \n You could be a fit if you have:\n \n Staff-Level Expertise: 7+ years of hands-on UX research experience in complex B2B, developer, or enterprise software environments, with a track record of driving product impact at a Senior or Staff level.\n Mixed-Methods Research Knowledge: Demonstrated equal mastery across Qualitative and Quantitative research methodologies.\n AI Tool Practitioner: Active daily practitioner of AI tools and prompt workflows to streamline research processes and execution, including but not limited to synthesis, structuring unstructured data, and scaling insight delivery.\n Domain Experience: Experience with products made for developers, administrators, or other technical audiences; experience working on security products is a strong plus.\n Strategic Problem Solving: Strong ability to plan, prioritize, organize, and solve complex problems independently while working with technical and business constraints.\n Cross-Functional Communication: History of effective communication, storytelling, and alignment across all levels of leadership and cross-functional partners (Product, Design, ML Engineering, Data Science).\n Mentorship \u0026 Leadership: Voracious learner and coach to people around you, raising the methodological and technical bar for the team.\n Education: Master’s or Ph.D. in Human-Computer Interaction (HCI), Cognitive Psychology, Computer Science, Data Science, Social Sciences, or equivalent industry experience.\n \n Nice-to-Have  (Not required, but a plus):\n \n Advanced Quantitative Toolkit: SQL, R or Python, Cluster Analysis, Advanced Statistical Modeling, A/B Testing.\n AI Systems \u0026 Ops: Human-in-the-Loop (HITL) UX Evaluation, Advanced Prompt Engineering for Ops, Agentic Workflow Evaluation, Synthetic Data Validation.\n \n  \n #LI-Hybrid #LI-MM P16119_3519938\n The annual base salary range for this position for candidates located in the San Francisco Bay area is between: \n $174,000 — $240,000 USD \n Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: https://rewards.okta.com/us .    \n The annual base salary range for this position for candidates located in California (excludi","salary_min":140000,"salary_max":192000,"location":"Bellevue, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","fine-tuning","healthcare","research"],"apply_url":"https://www.okta.com/company/careers/opportunity/8128490?gh_jid=8128490","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-14T15:52:40Z","expires_at":"2026-09-30T13:39:59.366609Z","created_at":"2026-08-25T18:29:14.516704Z","updated_at":"2026-08-31T13:39:59.503343Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3c301340-19ad-4a31-8d61-d1c8287d1477"},{"id":"7b9b8809-f3ac-4c1b-9808-82ec279c5fb4","company_id":"a0000000-0000-0000-0000-000000000001","title":"Software Engineer, Infrastructure, Interpretability","slug":"software-engineer-infrastructure-interpretability-3cb5ab0f","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 When you see what modern language models are capable of, do you wonder, \"How do these things work? How can we trust them?\"\n The Interpretability team at Anthropic works to understand what's actually happening inside trained models - and applies our best techniques to keep frontier AI safe as it rapidly improves.\n Think of us as doing \"neuroscience\" of neural networks using \"microscopes\" we build - or reverse-engineering neural networks like binary programs.\n More resources to learn about our work: \n \n \n Our Research blog - covering advances including Monosemantic Features and Circuits \n \n An Intro to Interpretability from our research lead, Chris Olah \n \n The Urgency of Interpretability from CEO Dario Amodei\n \n Engineering Challenges Scaling Interpretability - directly relevant to this role\n \n 60 Minutes segment - see a demo of tooling our team built\n \n New Yorker article - what it's like to work on one of AI's hardest open problems\n \n This role is an early hire on a new infrastructure effort within Interpretability: you'll help define its charter, not just execute it. \n Interpretability research requires deep access to frontier models while retaining a high degree of research flexibility. Your job is to build the paved path that makes that access secure by default, private by design, and low-friction for every researcher. The work spans four areas:\n \n \n Security : design the secure-by-default environments and access patterns that enable deep model access for an organization whose research requires it - done well, the same design improves both our security posture and research productivity.\n \n Privacy : build data-access patterns that ensure policy adherence as our research moves from theory into practical application\n \n Data \u0026 Compute Management : manage research data at petabyte scale and make efficient use of large accelerator fleets - storage lifecycle, capacity planning, and scheduling.\n \n Developer experience : agentic engineering, tooling and observability that keep researchers moving fast\n \n In this role, you’ll be deeply embedded alongside Interp Researchers to understand their workflows - building your understanding of the research as you go; at the same time you’ll bridge communication with Anthropic’s wider platform and security teams.. Every hour of researcher friction you remove is multiplied across the whole organization, and the infrastructure you build sets the pace at which interpretability results reach real safety decisions.\n Responsibilities:\n \n \n Design, build, and own shared infrastructure for Interpretability - research environments, data systems, and compute tooling that researchers rely on daily\n \n Lead cross-team efforts with our agentic engineering , security, compute, and storage platform teams, so that company-wide solutions serve research needs\n \n Discover and resolve major organization-wide developer experience issues\n \n Help take interpretability methods from research code to dependable audit pipelines\n \n You may be a good fit if you:\n \n \n Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python\n \n Have significant experience building and operating secure and scalable software infrastructure - cloud systems, distributed systems, or developer tooling\n \n Have strong cross-functional communication skills - equally at home working with researchers and with platform and security teams\n \n Are extremely curious about unfamiliar domains\n \n Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions\n \n Are curious about interpretability research and its role in AI safety (though no research experience is required!)\n \n Care about the societal impacts and ethics of your work\n \n Strong candidates may also have:\n \n \n Experience with cloud infrastructure (e.g. GCP or AWS), Kubernetes, networking and infrastructure-as-code\n \n Security engineering experience: identity / auth / access management, sandboxing, red teaming\n \n Experience with data warehousing, large-scale storage systems, and data lifecycle management - especially for research\n \n Experience with compute schedulers and accelerator fleet management\n \n Experience building developer productivity tooling and observability stacks\n \n Experience building tooling to accelerate research teams\n \n Representative Projects:\n \n \n Design and stand up a hardened research environment where researchers experiment directly on frontier model weights\n \n Build lifecycle management for petabytes of research data - visibility, retention, and cost efficiency\n \n B","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["alignment","distributed-systems","cloud","deep-learning","security","agents","infrastructure","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5388612008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T22:29:15Z","expires_at":"2026-09-30T13:30:37.194536Z","created_at":"2026-08-25T18:26:19.069491Z","updated_at":"2026-08-31T13:30:37.317078Z","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/7b9b8809-f3ac-4c1b-9808-82ec279c5fb4"},{"id":"b622f8c2-d6ae-4c56-af48-a73a0563caa1","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Researcher, Cybersecurity Products","slug":"staff-researcher-cybersecurity-products-6eb1c07e","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 We're looking for a Capabilities Researcher to join the team building Claude Security. In this role, you'll identify which security capabilities in frontier models are ready to build on, measure how well they perform, and work out how to make them useful to customers who are not security experts.\n Frontier models have become substantially more capable at security work over recent generations, and they continue to improve with each release. That progress creates a set of practical questions: which capabilities are reliable enough to depend on, how they perform in realistic conditions, how they behave when an adversary is involved, and where their limits are. You'll be responsible for answering those questions through fast prototyping and rigorous evaluation, and your findings will shape what the team decides to build.\n You'll also work on making those capabilities usable. Together with engineers on the team, you'll design the scaffolding, tooling, and defaults that let a strong model capability do useful work for a non-expert, and you'll stay involved as it becomes a product.\n This is a research role on a product team, with a broad charge and real latitude in what you investigate. It suits someone who already has ideas about what AI should be able to do for security teams and wants the models, the time, and the engineering support to pursue them.\n Responsibilities \n \n Prototype rapidly to find define the AI frontier for cybersecurity work\n Design evaluations that measure model performance on the work security teams actually do\n Build the datasets, harnesses, and scoring those evaluations depend on\n Engage with the cybersecurity community to help define where AI can make the most impact\n Work with engineers and researchers to operationalize promising capabilities into something customers can rely on\n Track how model capabilities for security are changing, and what that means for what we build next\n Share findings that inform product direction, and partner with product leadership on priorities\n \n You may be a good fit if you: \n \n Have deep expertise in one or more security domains, such as vulnerability research, exploit development, reverse engineering, malware analysis, incident response, or offensive security\n Have built AI-powered tools or capabilities for security work\n Can get from an idea to a working prototype quickly, and abandon the ones that don't hold up\n Are comfortable designing rigorous evaluations and interpreting the results honestly\n Can write and communicate clearly about technical findings\n Have 7+ years of experience in security research, security engineering, or a closely related field\n \n Strong candidates may also have: \n \n Published research, CTF results, CVEs, or open source security tooling\n Experience with model evaluation, benchmarking, or red teaming\n Experience building agentic applications\n Familiarity with the safety considerations of AI in security contexts\n \n Deadline to apply: None. Applications will be reviewed on a rolling basis.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $405,000 — $485,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like","salary_min":405000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["alignment","agents","security","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5385217008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-11T16:49:22Z","expires_at":"2026-09-30T13:30:38.53503Z","created_at":"2026-08-25T18:26:19.438759Z","updated_at":"2026-08-31T13:30:38.6565Z","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/b622f8c2-d6ae-4c56-af48-a73a0563caa1"},{"id":"580a6222-e4a4-4460-b448-7037234c34fb","company_id":"ab3e4567-6f87-4ccf-9ec0-81fd82105f48","title":"AI Security Research \u0026 Red Team Engineer","slug":"ai-security-research-red-team-engineer-3e1e62b9","description":"About Us\n At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.\n At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a \"normalized\" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.\n The Role: \n We are seeking a highly skilled AI Security Research \u0026 Red team engineer  to join our Red Team within the Security Threat Detection, Response and Emulation organization. This is a critical role that will be at the forefront of protecting our company and customers from malicious threats. You will be responsible for driving security research, exercises, and activities that emulate real world attackers and attacks to drive improvements in Cloudflare’s security posture focusing on AI, Agents, harnesses and LLM’s. \n Key Responsibilities: \n \n AI Security and Vulnerability Research: Stay current with emerging threats and perform deep-dive research to identify AI-specific vulnerabilities and risks in addition to general vulnerabilities across Cloudflare’s products and services.\n Agentic testing and adoption: As a core function, identifying AI-related attack surfaces through rigorous testing of agentic implementations and LLM usage which will help  define requirements and implementation guidance while proactively. \n Adversary Simulation: Execution of full-chain red team operations targeting Cloudflare’s global infrastructure, corporate networks, and product ecosystems.\n Efficacy Testing: Establish a rigorous framework for testing \"Security Efficacy\"—measuring exactly how well our WAF, EDR, and SIEM detections perform against known TTPs (Tactics, Techniques, and Procedures).\n Purple Teaming: Foster a highly collaborative relationship with the Blue Team (Detection \u0026 Response) to ensure findings are translated into immediate defensive improvements.\n Mentorship \u0026 Growth: Be a technical leader, providing technical expertise while fostering a culture of curiosity, ethical hacking and partnering to improve Cloudflare’s security posture. \n Executive Reporting: Translate complex technical exploits into risk-based narratives for leadership, helping prioritize engineering resources where they matter most.\n \n Partnerships \n \n Security Incident Response Team (SIRT): You will act as the \"sparring partner\" for SIRT. By conducting unannounced exercises, you help them refine their playbooks, test their on-call rotations, and ensure their forensic tooling is effective under pressure.\n Threat Detection \u0026 Threat Engineering: You will partner closely with these teams to bridge the gap between adversary simulation and defensive coverage. You will proactively identify detection gaps, lead the development of new detection logic, and establish rigorous validation frameworks to test and tune detections against emerging TTPs.\n Product Engineering/SRE: We operate as \"Customer Zero\" of our own products, your red teaming findings will drive resilience in processes and implementations, ultimately making Cloudflare and its customers more secure.\n Governance, Risk, and Compliance (GRC): You will bridge the gap between \"paper security\" and \"technical reality.\" By providing empirical evidence of control effectiveness, you help GRC move away from manual audits and toward continuous, automated compliance validation.\n \n Required Qualifications: \n \n Experience: 4+ years in offensive security, application security or other relevant field\n Deep knowledge:  AI, Coding agents, LLMs, prompt engineering, AI-related attack vectors (e.g., prompt injection, jailbreaking), and Agentic concepts all for use in the red team but also testing Cloudflare  uses.\n Technical Roots: A strong background in manual p","salary_min":166000,"salary_max":208000,"location":"Hybrid","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["alignment","agents","llm","cloud","security","research"],"apply_url":"https://boards.greenhouse.io/cloudflare/jobs/8097321?gh_jid=8097321","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-10T15:02:09Z","expires_at":"2026-09-30T13:39:54.074028Z","created_at":"2026-08-25T18:29:12.682572Z","updated_at":"2026-08-31T13:39:54.214272Z","company_name":"Cloudflare","company_slug":"cloudflare","company_logo_url":"https://www.google.com/s2/favicons?domain=cloudflare.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/580a6222-e4a4-4460-b448-7037234c34fb"},{"id":"71596059-a8ad-4f1d-9c9b-7e4d5d7211e7","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior Research Scientist, Target Tracking","slug":"senior-research-scientist-target-tracking-db0e53e3","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","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","payments","computer-vision","research"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5207730007?gh_jid=5207730007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-10T01:28:08Z","expires_at":"2026-09-30T13:37:37.077494Z","created_at":"2026-08-25T18:28:19.380128Z","updated_at":"2026-08-31T13:37:37.201399Z","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/71596059-a8ad-4f1d-9c9b-7e4d5d7211e7"},{"id":"5be4d9af-6e30-4dae-9205-9bd74663893b","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Research Scientist, Battlespace Awareness","slug":"research-scientist-battlespace-awareness-d2cc6f0e","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 $126,000 — $167,000 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":126000,"salary_max":167000,"location":"Broomfield, CO","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["computer-vision","cloud","payments","research"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5207729007?gh_jid=5207729007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-10T01:28:07Z","expires_at":"2026-09-30T13:37:33.177595Z","created_at":"2026-08-25T18:28:19.19072Z","updated_at":"2026-08-31T13:37:33.298897Z","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/5be4d9af-6e30-4dae-9205-9bd74663893b"},{"id":"3f258c6a-83b2-4130-811d-31eff5185f47","company_id":"9fc548e8-c877-41bb-95cf-286d95cce95f","title":"Software Engineer","slug":"software-engineer-2e642199","description":"WE ARE AN APPLIED AI LAB BUILDING END-TO-END SOFTWARE AGENTS.\n\nWe're the makers of Devin, the first AI software engineer. \n\nOur team is extremely talent-dense. Among our founding team, we have world-class competitive programmers, former founders, and leaders from companies at the cutting edge of AI including Scale AI, Palantir, Cursor, Waymo, Tesla, Lunchclub, Modal, Google DeepMind, and Nuro.\n\nBuilding Devin is just the first step—our hardest challenges still lie ahead. If you’re excited to solve some of the world’s biggest problems and build AI that can reason on real-world tasks, apply to join us.\n\n\nROLE MISSION\n\nSoftware Engineers at Cognition are not feature builders. You will be working on some of the hardest open problems in applied AI: how do you build an agent that can reason across thousands of lines of code, spawn and coordinate subagents, use tools reliably across ambiguous long-horizon tasks, and do all of this in a way that a real engineer would trust? You will ship systems that go directly into Devin and Windsurf, two products that millions of developers use to write, debug, and ship code. This is a role for engineers who want to be close to the frontier, who can move fast without cutting corners, and who believe the next 5 years of software engineering will look fundamentally different from the last 5.\n\n\n\n\nWHAT YOU'LL ACCOMPLISH\n\n - Build core agent infrastructure: Design and ship the systems that power Devin's long-horizon task execution: tool use, context management, multi-step planning, subagent orchestration, and sandboxed code execution environments.\n\n - Improve Windsurf as an AI-native IDE: Contribute to editor intelligence, agent-in-the-loop workflows, real-time code understanding, and the developer experience that makes Windsurf different from every other IDE.\n\n - Close the loop between models and products: Work directly with researchers to translate new model capabilities into shipped features; your feedback shapes what gets prioritized in training.\n\n - Own reliability and performance at scale: Build systems that handle millions of agentic tasks with low latency, high reliability, and the kind of correctness that developers depend on in production.\n\n - Move the category forward: Cognition is defining what AI software engineering looks like. You will have real input into what gets built next and why.\n\n\n\n\nEXCEPTIONAL CANDIDATES HAVE DEMONSTRATED\n\n - Systems engineering depth: Experience building reliable, performant distributed systems; you have strong opinions about correctness, failure modes, and production behavior.\n\n - Product instinct: You care about how the software you build feels to use and you have shipped things that real people depend on.\n\n - Comfort with ambiguity: You can make progress on hard problems with incomplete specs, learn fast from results, and course-correct without needing a lot of direction.\n\n - Velocity without shortcuts: A track record of shipping quickly while maintaining the kind of code quality that a high-density team expects.\n\n - Curiosity about agents and AI: You have dug into how LLMs work, how agents fail, and what it takes to make AI-powered systems behave reliably in the real world.\n\n - Strong Python proficiency: Python is the primary language across Cognition's codebase; you write clean, well-structured Python and are comfortable owning large Python codebases in production.\n\n - Relevant industry experience: Prior experience at a frontier AI lab, applied AI company, or developer tools company; you know what good looks like in this category.\n\n - Degree from a top-tier university: BS, MS, or equivalent in Computer Science, Mathematics, Engineering, or a related technical discipline from a highly selective program.\n\n\n\n\nCOMPENSATION \u0026 BENEFITS\n\n - Base Salary: $260,000 - $300,000 + Significant early-stage equity\n\n - Medical, Dental, Vision: Fully paid for you and your dependents\n\n - 401(k): Company match included\n\n - Perks: Private chef, cozy slippers, endless snacks, and more\n\n\nEQUAL OPPORTUNITY\n\nCognition is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. We are committed to providing reasonable accommodations for candidates with disabilities throughout the hiring process - please let us know if you need any.","salary_min":260000,"salary_max":300000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","llm","agents","research"],"apply_url":"https://jobs.ashbyhq.com/cognition/e8086415-62bc-4cc0-96a4-84bb56182d35/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-06T18:11:41.5Z","expires_at":"2026-09-30T13:33:21.561393Z","created_at":"2026-04-13T09:38:18.732512Z","updated_at":"2026-08-31T13:33:21.690259Z","company_name":"Cognition","company_slug":"cognition","company_logo_url":"https://www.google.com/s2/favicons?domain=cognition.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3f258c6a-83b2-4130-811d-31eff5185f47"},{"id":"3340f5ff-d88b-404f-8c05-fdcc45135ac2","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Principal Research Scientist, Robot Foundation Model","slug":"principal-research-scientist-robot-foundation-model-33c1630c","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The Role \n We are looking for a Principal Research Scientist to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Science as a founding member.\n MEGA is building foundation models for general-purpose robots beyond self-driving vehicles. Our focus is on creating intelligent agents that can perceive, reason, move and manipulate the physical world across diverse embodiments, including mobile manipulators, dual-arm platforms and humanoids.\n This is a senior, high-impact role with genuine 0→1 ownership . You will help define the research agenda, technical strategy and foundations of a new robotics program, working alongside world-class researchers in foundation models, embodied intelligence and large-scale machine learning.\n You will have the opportunity to work across the entire robot-learning stack: building scalable data flywheels, developing new model architectures and learning algorithms, training large models, designing rigorous evaluations and deploying policies on real robots. The goal is work on compelling and publishable research, but also to turn it into systems that demonstrate increasingly general, robust and useful behavior in the physical world.\n Your day-to-day work may span vision-language-action models, world and action models, multimodal and omni models, video generation, reinforcement learning, imitation learning and behavioral cloning. You will work with large-scale video and robotics datasets, distributed training infrastructure and a growing fleet of physical platforms.\n You will collaborate closely with researchers, ML engineers, roboticists and hardware teams to move ambitious ideas rapidly from research hypotheses to large-scale experiments and impressive real-world capabilities.\n This is a rare opportunity to help build a general robotics effort from the ground up—combining frontier foundation-model research with the immediacy and complexity of intelligence embodied in real machines.\n Key Responsibilities \n \n Lead research into architectures, data and learning approaches for robot foundation models.\n Design, implement and evaluate models such as VLAs, WAMs, omni-modal models, video models and related foundation-model architectures for robotics.\n Explore and develop learning approaches including reinforcement learning, behavioural cloning and other methods relevant to robot policy development.\n Synthesize, curate and filter large-scale video datasets for model training and evaluation.\n Build and use scalable distributed training pipelines and infrastructure for large models and large datasets.\n Influence and/or own technical decisions around robot policy development, data strategy and model design.\n Collaborate closely with scientists, engineers and robotics teams to connect research progress to real-world robot performance.\n Communicate research clearly internally and, where appropriate, contribute to external publications and Wayve’s scientific presence.\n \n About You \n In order to set you up for success as a Principal Research Scientist at Wayve, we’re looking for the following skills and experience.\n Essential \n \n Deep experience in machine learning, with focus in one or more of: vision-language models, video models, robot policies, foundation models for robotics or embodied AI.\n Experience with scalable training, such as multi-node training, large datasets and/or large model training.\n Strong research track record, including publications in top-tier venues such as ICRA, CoRL, CVPR, NeurIPS, ICML or ICLR.\n Strong coding skills and hands-on experience with modern machine learning frameworks.\n Ability to design and drive an independent research agenda while collaborating closely with engineering and robotics teams.\n Experience translating research ideas into working systems, experiments or deployed capabilities.\n Strong communication skills and the ability to influence technical direction across teams.\n \n Desirable \n \n PhD in Computer Science, Machine Learni","salary_min":407000,"salary_max":512000,"location":"Sunnyvale, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["generative-ai","distributed-systems","robotics","computer-vision","autonomous-vehicles","reinforcement-learning","research"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8684066002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-06T09:23:33Z","expires_at":"2026-09-30T13:44:05.272007Z","created_at":"2026-08-25T18:31:14.339824Z","updated_at":"2026-08-31T13:44:05.387891Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3340f5ff-d88b-404f-8c05-fdcc45135ac2"},{"id":"d94df0a4-3277-4327-873b-ffebcbf38b69","company_id":"3dacb2af-b4b4-42ae-9b16-4e0203d290e4","title":"Staff Software Engineer, Operations Research","slug":"staff-software-engineer-operations-research-8a34b76c","description":"About Wing:  \n Wing offers drone delivery as a safe, fast, and sustainable solution for last mile logistics. Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google's parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you're ready to do the greatest work of your life, come join us. \n About the Role: \n Wing is looking for a Staff Software Engineer, Operations Research to join our Delivery Network team. This role is hybrid based in Palo Alto, CA .\n As a Staff Software Engineer, Operations Research, you will own the mathematical foundation of our delivery network. Moving physical goods through the sky autonomously introduces dynamic constraints: battery conditions, real-time weather patterns, airspace de-confliction, and shifting marketplace demand.\n You will dive into a wealth of flight and logistics data, using advanced optimization techniques to maximize value for our consumers, our partners, and our fleet. You will exercise independent judgment to define our technical roadmap and bridge the gap between abstract mathematical models and our production environment. You will leverage advanced solvers and simulations to build solutions that scale with Wing's business.\n What You’ll Do:  \n \n Design and Implement Algorithms: Build new algorithm components within our production delivery network system to meet emerging requirements. We work with Google OR-Tools and the researchers that develop it.\n Extract Data-Driven Insights: Analyze complex logistics data to identify network inefficiencies, translating those insights directly into production-ready algorithm enhancements.\n Integrate OR and ML: Combine state-of-the-art optimization and machine learning techniques (e.g., using ML for demand forecasting and Tools for fleet positioning) to improve the speed and quality of our dispatching decisions.\n Lead Cross-Functionally: Collaborate tightly with software engineers, data scientists, hardware teams, and product managers to develop scalable, cross-cutting solutions that balance physical constraints with business value.\n Exercise Strategic Autonomy: Evaluate technical options, make informed architectural decisions, and determine the appropriate OR methodologies to solve ambiguous, open-ended problems.\n Mentorship: Elevate the technical rigor of the team by guiding junior scientists and engineers in OR fundamentals, code quality, and algorithm design.\n \n What You’ll Need:  \n \n 12+ years of industry or post-graduate experience solving complex optimization problems using mathematical programming or metaheuristics.\n Ph.D. or Master's degree in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a closely related field.\n Strong coding ability in Python, C++, or Java. You must understand object-oriented programming, functional programming concepts, and core computer science algorithms.\n A proven track record of designing algorithms that don't just live in research papers, but operate efficiently in real-time production software systems.\n Previous experience in aviation, autonomous vehicles, ride-sharing, or last-mile logistics.\n Deep familiarity with other commercial or open-source optimization solvers (e.g., Gurobi, CPLEX, SCIP).\n Experience with cloud computing platforms (GCP, AWS) and integrating solvers into scalable, distributed systems.\n Experience modeling systems for simulation and designing experiments. We use a combination of discrete event simulations and high fidelity physics simulations.\n The US base salary range for this full-time position is the salary range below + bonus + equity + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process. \n Salary Range\n $274,000 — $292,000 USD \n Wing is an equal opportunity employer and it is Wing's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person's merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including bre","salary_min":274000,"salary_max":292000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","autonomous-vehicles","distributed-systems","research"],"apply_url":"https://wing.com/careers/8605187002?gh_jid=8605187002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T18:25:41Z","expires_at":"2026-09-30T13:49:04.365303Z","created_at":"2026-08-25T18:33:07.805882Z","updated_at":"2026-08-31T13:49:04.479357Z","company_name":"Wing","company_slug":"wing","company_logo_url":"https://www.google.com/s2/favicons?domain=wing.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d94df0a4-3277-4327-873b-ffebcbf38b69"},{"id":"abc5a118-dbe5-4818-85e9-01b7f09d7f5c","company_id":"a78ce7e7-7a7a-4474-97e2-c4ae4620275e","title":"AI Researcher - Post-Training (f/m/d)","slug":"ai-researcher-post-training-fmd-5164c0a3","description":"Who is Sonar?\nSonar is driving the future of agent-centric software development. As the leader in AI code verification and governance, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable.\nIntegrating seamlessly with Claude Code, Codex, Cursor, GitHub Copilot, Gemini, and Devin, we help over 75% of the Fortune 100 build trusted, reliable, compliant software. Customers who use Sonar are 44% less likely to report an outage due to AI-generated code.\nWe believe code verification is the critical missing link in the Agent-Centric Development Cycle (AC/DC). Industry giants like Nvidia, ServiceNow,Booking.com, Goldman Sachs, AstraZeneca, and Ford Motor Company count on us to provide independent, explainable, consistent review and governance of their AI-generated code via products like:\nSonarQube: The world’s leading AI code review and verification platform.\nSonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair.\nSonarSweep \u0026 Sonar Context Augmentation: Providing the enterprise-grade context and constraints agents need to be truly effective.\nOur team operates across global hubs in Austin, Bochum, Dubai, Geneva, London, Singapore, Tokyo, and Washington D.C. We move with a mindset we call CODE:\nCommitted to our customers and community.\nObsessed with quality.\nDeliberate in our decisions.\nEffective as one team.\nWith over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution. If you’re hungry to have an impact, want to build at a fast pace, and ready to work at the forefront of AI, we want to hear from you.\n\n\nPosition description\nAt Sonar, we are seeking an ambitious senior researcher to join our cross-disciplinary team, innovating and developing the next generation of solutions to build enterprise-grade coding agents and models. You will harness Sonar’s deep experience in static analysis, and combine it with your experience and leading techniques in large language model post-training. If you are interested in being hands-on with state-of-the-art research, building practical solutions that deliver high-impact for customers, and working within a team of innovative researchers and engineers, this role is for you.\n","salary_min":90400,"salary_max":166800,"location":"Bochum","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["llm","code-generation","agents","research"],"apply_url":"https://jobs.lever.co/sonarsource/44f5a3c9-d280-4f93-99f4-4e638491fbd6/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-05T16:21:11.456Z","expires_at":"2026-09-30T13:48:13.489534Z","created_at":"2026-08-25T18:32:49.227621Z","updated_at":"2026-08-31T13:48:13.596927Z","company_name":"SonarSource","company_slug":"sonarsource","company_logo_url":"https://www.google.com/s2/favicons?domain=sonarsource.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/abc5a118-dbe5-4818-85e9-01b7f09d7f5c"}],"page":1,"per_page":20,"total":728,"total_is_exact":true,"total_pages":37}