{"access":{"advertiser_pricing_url":"https://aidevboard.com/pricing","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","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"f47b2b52-9138-4056-a197-783873a96c39","company_id":"f5ee7284-a657-4da2-b351-cb806a3681cd","title":"Member of Technical Staff - Voice Model","slug":"member-of-technical-staff-voice-model-5b5f6cb9","description":"SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.  Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. \n ABOUT THE ROLE:\n You will join the Grok Voice Model team to help build the world’s best voice AI. We deliver smooth, natural, low-latency spoken interactions — expressive, multilingual, and reliable across devices and real-time scenarios. We own the full training pipeline: massive data curation, premium audio processing, frontier speech-language pre-training, and intensive post-training to push quality, speed, and stability to the limit.\n Our goal: make talking to AI feel like conversing with the most charming, kind, and knowledgeable person imaginable. We’re seeking exceptionally smart, execution-oriented engineers to help us get there.\n RESPONSIBILITIES:\n \n Design and execute large-scale speech data curation and processing pipelines, including collection of diverse real-world audio, synthetic data generation, and automated annotation workflows to enable high-quality model training and evaluation.\n Work on pre-training and post-training of speech-language models, with targeted enhancements through supervised fine-tuning, reinforcement learning, and other techniques to ensure Grok Voice responses are accurate, factually grounded, natural and idiomatic in spoken style, conversational in tone, and fluent across multiple languages.\n Build and iterate a comprehensive evaluation framework covering objective metrics (accuracy, quality, latency, expressiveness), human preference studies, content factuality assessments, real-time interaction quality, and experimentation infrastructure to measure and improve performance.\n Work closely with product teams to integrate voice models into applications and real-time environments, define spoken interaction specifications, and handle the full lifecycle from prototype to global-scale deployment for stable, low-latency, delightful voice experiences.\n \n BASIC QUALIFICATIONS:\n \n Python expert with deep proficiency in writing clean, efficient code for AI/ML systems.\n Hands-on experience processing large-scale datasets using tools like Spark and Ray for cleaning, augmentation, and feature extraction.\n Proficiency in pre-training and post-training speech-language models using JAX/PyTorch, including supervised fine-tuning, reinforcement learning, and optimizations for accuracy, factuality, natural spoken style, detail, and multilingual fluency.\n Ability to set up and run rigorous evaluation pipelines: objective metrics, human preference studies, content factuality checks, and iterative A/B testing to drive model improvements.\n Experience building or working with large-scale distributed training and inference systems on Kubernetes.\n Proactive, self-driven attitude — ready to grind in a fast-paced, high-caliber team to deliver outstanding voice AI experiences.\n \n COMPENSATION AND BENEFITS:\n $150,000 - $450,000 USD\n Base salary is just one part of our total rewards package at SpaceXAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short \u0026 long-term disability insurance, life insurance, and various other discounts and perks.\n SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .","salary_min":150000,"salary_max":450000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["speech","fine-tuning","reinforcement-learning","distributed-systems","pytorch","pre-training"],"apply_url":"https://job-boards.greenhouse.io/xai/jobs/5051966007","is_featured":true,"is_sticky":false,"status":"active","published_at":"2026-03-16T20:39:18Z","expires_at":"2026-08-14T14:04:44.897369Z","created_at":"2026-04-13T09:38:43.3144Z","updated_at":"2026-07-15T14:04:45.027875Z","company_name":"xAI","company_slug":"xai","company_logo_url":"https://www.google.com/s2/favicons?domain=x.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f47b2b52-9138-4056-a197-783873a96c39"},{"id":"66be6f1d-738c-4b9b-b07d-4cae69e7b29d","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Machine Learning Engineer, Agent Oversight","slug":"senior-machine-learning-engineer-agent-oversight-774633fc","description":"About Scale\n Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust.\n About the Team\n Applied Intelligence Systems team is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like.\n About the Role\n As a Machine Learning Engineer on Agent Oversight, you will drive the end-to-end lifecycle that ensures our production agents perform reliably and improve over time. This includes building observability tools, designing robust evaluation frameworks, and developing improvement loops. Whether scaling infrastructure or researching new improvement methods, you will navigate the entire ML loop while maintaining rigorous technical standards.\n You will:\n \n Build or contribute to observability into agent behavior in production — the signals and instrumentation needed to actually see what an agent is doing, not just whether it succeeded or failed\n Design evaluation methodologies and metrics for agentic applications, and work with the platform to make them run automatically, at scale, across different customer use cases, not just as one-off analyses\n Build, ship, and own ML systems that detect drift, anomalies, or misalignment in production agent behavior — from first prototype through running reliably at scale\n Design and run rigorous experiments to validate model and agent performance improvements before they ship\n Work alongside software engineers on the platform where your work intersects with broader infrastructure — but you’re expected to take your own work from idea to production, not hand it off\n Collaborate closely with product managers, customers, data annotators, Forward Deployed Engineers, and other engineering teams to translate enterprise and government requirements into robust platform capabilities\n Depending on focus, contribute to novel methods and approaches that push the state of the art for agent evaluation and improvement, or focus on building ML systems that hold up reliably at scale in production\n \n Requirements:\n \n 5+ years of experience as an ML engineer or applied scientist, ideally on a production ML or LLM-powered system — not just consuming a third-party ML API within a feature\n Strong grounding in  at least two  of the following:\n \n Building or scaling evaluation, monitoring, or continuous-learning infrastructure for ML/agentic systems\n Design experience for agent systems (architecture, orchestration, tool use)\n Developing new methods, reward models, or model training/fine-tuning approaches\n \n Hands-on experience with LLMs and agent architectures — tool use, planning, multi-agent orchestration\n Comfortable partnering with software engineers to productionize research and experimental work, not just deliver a one-off analysis\n Rigorous approach to experimentation: clear hypotheses, real statistical grounding, and results that hold up under scrutiny\n Track record of collaborating across functions (Product, Forward Deployed Engineering, etc.) to navigate ambiguous requirements and bring them to production\n Gives direct, substantive feedback on designs and code, and takes it the same way — and mentors others as they grow\n \n Nice to have:\n \n Experience building or contributing to RLHF, SFT, or other fine-tuning/RL workflows, reward modeling, or verifiable-reward systems\n Experience with model or systems optimization (e.g., latency, cost, or inference efficiency)\n Published research, open-source contributions, or patents in agentic systems, LLMs, or applied ML\n Experience working in regulated or enterprise contexts\n Track record of taking a novel method from prototype to something running reliably in production, navigating ambiguity along the way\n Experience reviewing others’ technical designs or mentoring engineers at a senior/staff level\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 level","salary_min":216000,"salary_max":270000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","llm","fine-tuning","agents","reinforcement-learning","autonomous-vehicles","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4714527005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T20:14:32Z","expires_at":"2026-08-14T14:01:47.147912Z","created_at":"2026-07-15T14:01:47.280877Z","updated_at":"2026-07-15T14:01:47.280877Z","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/66be6f1d-738c-4b9b-b07d-4cae69e7b29d"},{"id":"02fdc710-8e20-40fd-aedd-05f740fa50ac","company_id":"377b9ca2-ac79-48a5-8657-da630f9e447d","title":"Senior Staff / Principal Machine Learning Scientist, AI Inference \u0026 Optimization","slug":"senior-staff-principal-machine-learning-scientist-ai-inference-optimization-8c8ecaa7","description":"About Netskope \n Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. \n \n Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive.     Visit us at  Netskope Careers. Please follow us on LinkedIn and Twitter @Netskope . \n Positions are available at Senior Staff and above. Candidates are assessed individually and leveled according to their specific skills and background. \n About the role\n As a Senior Staff Machine Learning Scientist, you own the inference and optimization layer that makes AI in agentic workflows fast, efficient, and production-grade. You fine-tune and evaluate models, push latency and throughput on real hardware, and build the runtime that executes bounded AI tasks, validated against usage from Netskope’s large customer base so you optimize where the data points, not where you guess.\n What’s in it for you\n \n High-impact ownership. You own the model layer of a net-new product that changes the performance and economics of agentic AI.\n Cutting-edge, unusual stack. The hard, interesting inference problems live here: quantization, KV-cache and memory management, sparsity, fine-tuning, and hardware acceleration under real-world resource constraints.\n Real scale to build against. Netskope’s customer footprint gives you production signals most teams never see, so you deploy, validate, and iterate fast.\n \n What you will be doing\n \n Build and optimize the model inference path : quantization, KV-cache optimization, batching, and latency/memory/throughput tuning on constrained, commodity hardware.\n Fine-tune and evaluate models for bounded tasks; build eval harnesses that gate a capability to release on real accuracy, latency, and security relevance.\n Design and grow the task execution runtime (bounded sub-agents), pushing toward dynamic task generation and context compaction.\n Drive hardware acceleration / sparsity and support for larger models as the platform matures.\n Partner with the systems and backend engineers to ship capabilities end-to-end and iterate on real production signals.\n \n Required skills and experience\n \n 10+ years of overall industry experience , with 4+ years hands-on in ML/AI (model development, fine-tuning, and inference optimization).\n Hands-on with fine-tuning (e.g. LoRA/QLoRA), quantization (GGUF/AWQ/GPTQ), and inference runtimes (vLLM/SGLang, TensorRT-LLM, ONNX Runtime, llama.cpp, or MLX/CoreML). On-device or edge inference experience is a strong plus.\n Strong Python; comfort reaching into C++ for low-level interop is a plus.\n Solid grasp of transformer internals and the levers that move real inference performance and cost: KV cache, attention, batching, memory footprint.\n Fluency with agentic coding systems and genuine curiosity about agent harnesses like Claude Code, Pi, and Codex , so you should already be building with them, or itching to.\n Clear communication: able to distill a model or infra bottleneck into an actionable concept for cross-functional teammates.\n \n Education\n \n MS in Computer Science, Machine Learning, Electrical Engineering, or equivalent technical degree required, with a focus in AI/ML research; PhD in a related field strongly preferred.\n Compensation:  \n At Netskope, salary is one component of our competitive total rewards package. The salary range for this position is as listed below. This is a national range. For purposes of complying with applicable laws, the range applies to candidates in California, Colorado, Illinois, Maryland, New York, Washington, and other states. \n The successful candidate’s starting pay will also be determined based on job-related skills, experience, qualifications, location, and market conditions.  \n For all sales roles, the posted salary range is the On Target Earnings (OTE) range for the role, which is the sum of base salary and target commission amount at 100% goal achievement. \n In addition to salary, candidates may be eligible for other forms of compensation such as participation in a bonus plan (for non-sales roles) and a stock award program. Candidates may also be eligible for a comprehensive health plan and other benefits that can be reviewed at  Netskope Benefits site .","salary_min":182500,"salary_max":260500,"location":"San Jose, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["fine-tuning","agents","llm","cloud","machine-learning","inference"],"apply_url":"https://www.netskope.com/company/careers/open-positions/?gh_jid=8063869","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T04:20:32Z","expires_at":"2026-08-14T14:11:38.941823Z","created_at":"2026-07-15T14:11:39.076302Z","updated_at":"2026-07-15T14:11:39.076302Z","company_name":"Netskope","company_slug":"netskope","company_logo_url":"https://www.google.com/s2/favicons?domain=netskope.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/02fdc710-8e20-40fd-aedd-05f740fa50ac"},{"id":"7befba03-6985-475e-9441-9bd1ccb173d8","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Engineer, Chip Design RL (Reinforcement Learning)","slug":"research-engineer-chip-design-rl-reinforcement-learning-39e9d4d0","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the RL teams \n Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Fable 5 and Opus 4.8. Our work spans several key areas:\n \n Developing systems that enable models to use computers effectively\n Advancing code generation through reinforcement learning\n Pioneering fundamental RL research for large language models\n Building scalable RL infrastructure and training methodologies\n Enhancing model reasoning capabilities\n \n We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.\n About the role \n We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at.\n You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will: \n \n Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization.\n Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards.\n Conduct experiments and shape our roadmap.\n Deliver your work into research and production training runs.\n Collaborate with other researchers and engineers across and outside Anthropic.\n \n You may be a good fit if you: \n \n Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs.\n Are fluent with industry EDA tools and processes.\n Have taped out chips and have experience going from spec to silicon.\n Know how to balance research exploration with engineering implementation.\n Are passionate about AI's potential and committed to developing safe and beneficial systems.\n \n Strong candidates may also have: \n \n Experience with reinforcement learning, evaluations or environments.\n Built tooling or automation around chip design flows.\n Worked on ML accelerators or high-performance compute hardware.\n Familiarity with high-level synthesis or architecture simulators.\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 level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To","salary_min":500000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["code-generation","reinforcement-learning","fine-tuning","search","llm","alignment","agents","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5231612008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T22:19:12Z","expires_at":"2026-08-14T14:00:27.276583Z","created_at":"2026-07-15T14:00:27.407964Z","updated_at":"2026-07-15T14:00:27.407964Z","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/7befba03-6985-475e-9441-9bd1ccb173d8"},{"id":"26f6fd92-b550-42db-86b5-5699c2c31afc","company_id":"75dcf7c0-5121-45f1-8d1b-6bfbfe15072f","title":"Helix AI Engineer, Localization and Mapping","slug":"helix-ai-engineer-localization-and-mapping-9de55455","description":"Figure is on a mission to develop and deploy general purpose humanoid robots for corporate tasks targeting labor shortages and jobs that are undesirable or unsafe. We are looking for passionate and motivated superstars to grow our world-class team. We are based in Sunnyvale, CA and require 5 days/week in-office collaboration. It’s time to build.\n Figure’s vision is to deploy autonomous humanoids at a global scale. Our AI team is looking for Localization and Mapping Engineers to empower Figure humanoid robots to perform highly dynamic operations in demanding real-world environments.\n Responsibilities: \n \n Architect and implement real-time localization, ego-motion tracking, and state estimation systems by fusing multi-modal sensor data (cameras, IMUs, encoders, magnetic sensors).\n Build and maintain scalable, offline pose-tracking pipelines to process large-scale training data from diverse sources.\n Develop and optimize multi-sensor calibration systems for humanoid robotics and data collection platforms.\n Partner with cross-functional teams to build comprehensive, data-driven evaluation and testing frameworks.\n Design, engineer, and deploy high-quality, reliable software solutions for real-world robotics applications.\n \n Required Qualifications: \n \n Deep technical expertise in solving complex estimation and nonlinear optimization problems.\n Strong command of 3D geometry, visual-inertial SLAM, and computer vision techniques, including feature matching/tracking, and Structure from Motion (SfM).\n Experience writing performant C++ software.\n Hands-on experience with sensor calibration (e.g., multi-camera and IMU intrinsics/extrinsics).\n Ability to thrive in a fast-paced, ambiguous environment that requires rapid exploration and iteration.\n Passion for advancing humanoid robotics technology.\n \n Bonus Qualifications: \n \n Experience implementing visual-inertial SLAM systems on legged robotic platforms.\n Background in estimation problems related to human motion capture or AR/VR applications.\n Experience applying state-of-the-art Deep Learning approaches to SLAM, 3D reconstruction, or human pose estimation.\n \n The US base salary range for this full-time position is between $200,000 - $400,000\n The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.","salary_min":200000,"salary_max":400000,"location":"San Jose, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["computer-graphics","computer-vision","fine-tuning","deep-learning","robotics"],"apply_url":"https://job-boards.greenhouse.io/figureai/jobs/4696533006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T16:02:44Z","expires_at":"2026-08-14T14:07:52.541231Z","created_at":"2026-07-15T14:07:52.665427Z","updated_at":"2026-07-15T14:07:52.665427Z","company_name":"Figure AI","company_slug":"figure-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=figure.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/26f6fd92-b550-42db-86b5-5699c2c31afc"},{"id":"58ddb548-32cb-47ff-9778-f85baf797bcf","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Data Engineer, Public Sector","slug":"senior-data-engineer-public-sector-8cb646e9","description":"Senior Data Engineer, Public Sector\n As a Data Engineer for the Public Sector business unit, you will build Scale's analytical and business-intelligence infrastructure. Scale's customers process millions of tasks through our APIs, and we're looking for a talented Data Engineer to build scalable solutions to support this growth. You will have widespread purview, with responsibility for understanding, mining, aggregating, and exposing data across the entire business unit to support timely and efficient decision-making and data exploration. You will also implement Scale's data warehouse, data mart, and business intelligence reporting environments, and help users transition their workflows to these systems. \n This role requires collaboration with leadership and cross-functional teams to solve complex problems and develop sustainable, scalable data solutions. Your responsibilities will include both ad-hoc analyses and the creation of core data models and pipelines, directly impacting how Scale operates and evaluates its performance.\n You will:\n \n Work with operations, finance, and engineering to drive the development of pipelines that provide single-source-of-truth foundational accuracy\n Continually improve ongoing data pipelines and simplify self-service support for business stakeholders\n Perform regular system audits, and create data quality tests to ensure complete and accurate reporting of data/metrics\n Develop repeatable, scalable analytical solutions, such as data models, improved pipelines, or better underlying tables\n Have an active Secret security clearance (Top Secret preferred) \n \n Ideally You’d Have:\n \n 5+ years of relevant work experience in a role requiring application of data modeling and analytic skills\n Ability to create extensible and scalable data schema and pipelines that lay the foundation for downstream analysis\n Mastery of SQL and relational databases; experience with programming languages (e.g., Python/R)\n Experience building a reliable transformation layer and pipelines from ambiguous business processes using tools such DBT to create a foundation for data insights\n \n  \n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n The base salary range for this full-time position in the location of Washington DC is:\n $150,400 — $259,000 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. \n We believe that everyone 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 collect, retain and use personal d","salary_min":150400,"salary_max":259000,"location":"Washington, DC","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","data-pipeline","data-engineering","data-science"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4713597005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-11T02:29:10Z","expires_at":"2026-08-14T14:01:46.806174Z","created_at":"2026-07-12T14:01:20.981859Z","updated_at":"2026-07-15T14:01:46.933728Z","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/58ddb548-32cb-47ff-9778-f85baf797bcf"},{"id":"390fea98-a9ba-4487-890a-77d135398888","company_id":"19955a21-2cd6-41fd-a4a8-19b7a942ac16","title":"Lead Value Engineer - Life Sciences","slug":"lead-value-engineer-life-sciences-4c32b22b","description":"Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.\n \n Role Description \n As a Lead Value Engineer specializing in the Life Sciences, you are pushing the envelope in solving business-critical problems for the world's largest, most diversified life science organizations. You will be working intimately with this strategic client, understanding their uniquely complex objectives—spanning from logistics to the precision distribution of advanced products—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks)..\n With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers’ supply chain networks and enables them to industrialize AI. This unlocks real ROI on AI deployments at scale, ensuring life-saving products reach patients faster and safer. There is no AI without PI. You will prototype these solutions, demonstrate their value to Chief Supply Chain Officers (CSCOs) and operational leaders, and ensure successful implementation, adoption, and value realization to increase the footprint of Celonis across the life sciences sector.\n Key Responsibilities \n \n \n AI Discovery \u0026 Solutioning: Understand the client's overarching AI strategy and the distinct supply chain challenges across both their MedTech portfolios (e.g., mitigating global raw material shortages, optimizing supply chains, managing inventories, or accelerating quality batch releases). As a Celonis product and life sciences domain expert, translate these complex, multi-tiered logistics requirements into innovative AI solutions that drive measurable impact..\n \n Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds in the supply chain are successfully reached.\n \n Hackathons \u0026 Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex, fragmented supply chain networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points in planning, sourcing, manufacturing, and distribution.\n \n Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., autonomous inventory rebalancing or intelligent shipment exception handling).\n \n Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise ERPs (e.g., SAP), Quality Management Systems (QMS), and strict regulatory frameworks (FDA, EMA, GxP).\n \n Domain \u0026 Industry Leadership: Serve as the internal and external technical subject matter expert for the Life Sciences Supply Chain, scaling knowledge across the organization regarding pharmaceutical manufacturing and logistics processes.\n \n Requirements \n \n \n 8+ years of experience leading technical pre-sales and post-sales engagements specifically within Life Sciences, Pharmaceutical, or MedTech supply chains. This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.\n \n Deep understanding of supply chain business processes native to Life Sciences (such as Sales \u0026 Operations Planning (S\u0026OP), Procure-to-Pay, Track \u0026 Trace, Cold Chain Management, or Quality Control/Batch Release) with the ability to translate high-level business needs into specific AI use cases.\n \n Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent chatbots for supplier collaboration, automated extraction of data from complex customs or quality documents).\n \n Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and techn","salary_min":157000,"salary_max":184000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","generative-ai","fine-tuning","llm","agents","cloud"],"apply_url":"https://job-boards.greenhouse.io/celonis/jobs/7800529003?gh_jid=7800529003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T21:19:52Z","expires_at":"2026-08-14T14:10:27.060437Z","created_at":"2026-07-12T14:07:50.167193Z","updated_at":"2026-07-15T14:10:27.247076Z","company_name":"Celonis","company_slug":"celonis","company_logo_url":"https://www.google.com/s2/favicons?domain=www.celonis.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/390fea98-a9ba-4487-890a-77d135398888"},{"id":"78bb5e81-4dfe-4ed2-af4d-f819687a5629","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Cloud Infrastructure Architect, Okta Federal","slug":"cloud-infrastructure-architect-okta-federal-be26a5b7","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 \n  Technology, Data, and Insights (TDI) is on a mission to accelerate Okta's scale and growth. We bring world-class business acumen and technology expertise to every interaction. We also drive cross-functional collaboration and are focused on delivering measurable business outcomes.\n The TDI Infrastructure Engineering team owns the foundational platforms that power Okta's business — from cloud infrastructure and AI platform delivery to network engineering, developer productivity, observability, and client platforms. We are a team of builders who design and operate at scale, and we are in the middle of a strategic transformation: evolving our cloud practice from a self-service model into a managed, opinionated platform that the entire business can rely on.\n The Cloud Platform Architect Opportunity\n Okta Federal, Inc. is looking for a dedicated Cloud Platform Architect for TDI Infrastructure Engineering — the technical authority for how we design, build, and evolve the cloud infrastructure that underpins our AI platform and the broader workloads running across the business. You will define the architectural standards, patterns, and strategies that the Cloud Platform Engineering team builds to, and you will serve as a key partner to AI, security, and productivity architects as we scale Okta's cloud capabilities to meet increasing business demand.\n This is a hands-on builder role. We are not looking for someone who advises from a distance — we need someone who has shipped cloud infrastructure at scale and brings the credibility and depth to make sound architectural decisions in a fast-moving environment. You will operate at a critical moment: Okta's AI platform is scaling rapidly, our cloud platform team is transforming, and the foundational decisions made now will define the trajectory of our infrastructure for years.\n This role reports directly to the Director of Infrastructure Engineering.\n What You'll Be Doing\n \n Define and own Okta's Cloud Platform architecture — establish reference architectures, design standards, and guardrails that bring consistency, security, and reliability to workloads running across the business\n Lead the architecture for Kubernetes and EKS — design and evolve our cluster strategy, multi-tenancy model, networking topology, and security posture as the platform scales to support AI agent workloads and diverse business unit deployments\n Elevate Okta's AI platform — partner with AI architects and platform engineers to evolve our agent and model-serving infrastructure from its current state to a production-grade, scalable platform capable of supporting broad business adoption\n Drive multi-cloud strategy — build the evaluation framework and decision criteria for when and how Okta leverages AWS, Azure, and Google Cloud; ensure workload placement is intentional and optimized for performance, cost, and capability\n Serve as the technical anchor for the Cloud Platform Engineering team — raise the architectural quality of everything the team designs and builds as we complete the transformation from account vending to a managed platform model\n Partner cross-functionally with AI, security, and productivity architects, product managers, and business unit stakeholders to ensure cloud infrastructure decisions align with Okta's product, compliance, and operational requirements — including support for federal programs and FedRAMP environments\n Partner cross-functionally to design cloud-native solutions that can be effectively adapted for air-gapped, self-hosted environments like US Secret (SIPRNet) and US Top Secret (JWICS).\n Help architect and validate foundational Kubernetes and infrastructure designs within unclassified AWS GovCloud sandboxes. You will ensure these commercial-side designs translate seamlessly when tested against emulators that simulate the strict constraints of air-gapped networks.\n Ensure our commercial cloud platform architecture shares foundational DNA with our highly regulated deployments, aligning with DoD-centric frameworks like the USAF's \"Big Bang\" architecture and utilizing Iron Bank hardened containers where applicable.\n \n What You'll Bring to the Role\n \n 10+ years of hands-on cloud infrastructure experience with deep, demonstrated expertise in one or more major cloud providers (AWS, GCP, or Azure) — including compute, networking, storage, IAM, and managed services at enterprise scale; AWS experience is preferred given our current environmen","salary_min":244000,"salary_max":336000,"location":"Washington, DC","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","mlops","cloud","agents","data-pipeline","embeddings","infrastructure"],"apply_url":"https://www.okta.com/company/careers/opportunity/8004104?gh_jid=8004104","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T17:52:28Z","expires_at":"2026-08-14T14:11:18.197322Z","created_at":"2026-07-10T14:08:46.130561Z","updated_at":"2026-07-15T14:11:18.324586Z","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/78bb5e81-4dfe-4ed2-af4d-f819687a5629"},{"id":"9b918972-172d-4cf7-bea5-24effecf6a52","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-69ed84ad","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Boston, MA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","cloud","generative-ai","fine-tuning","robotics","data-pipeline","llm","rag"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799671003#/7799671003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:05Z","expires_at":"2026-08-14T14:07:59.682275Z","created_at":"2026-07-10T14:05:50.176304Z","updated_at":"2026-07-15T14:07:59.82836Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9b918972-172d-4cf7-bea5-24effecf6a52"},{"id":"9cb51051-fb08-47c1-a84d-e0937ebe010e","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-50d09b91","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Las Vegas, Nevada, United States","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","robotics","data-pipeline","generative-ai","cloud","rag","fine-tuning","autonomous-vehicles"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799673003#/7799673003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:04Z","expires_at":"2026-08-14T14:07:59.867702Z","created_at":"2026-07-10T14:05:50.099596Z","updated_at":"2026-07-15T14:07:59.996378Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9cb51051-fb08-47c1-a84d-e0937ebe010e"},{"id":"bd8a325e-af13-4567-9c46-1409196e7f88","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-8c5b455c","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","generative-ai","fine-tuning","rag","llm","autonomous-vehicles","cloud","robotics"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799677003#/7799677003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:03Z","expires_at":"2026-08-14T14:07:59.503144Z","created_at":"2026-07-10T14:05:50.334397Z","updated_at":"2026-07-15T14:07:59.735842Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bd8a325e-af13-4567-9c46-1409196e7f88"},{"id":"e651da08-bc17-4c8c-b426-19a46cba7f02","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-65385fb7","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["rag","fine-tuning","robotics","generative-ai","data-pipeline","embeddings","llm","cloud"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799653003#/7799653003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:01Z","expires_at":"2026-08-14T14:07:59.77536Z","created_at":"2026-07-10T14:05:50.254594Z","updated_at":"2026-07-15T14:07:59.919958Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e651da08-bc17-4c8c-b426-19a46cba7f02"},{"id":"1a986b20-b2ab-4938-b3d5-5fcbbdc73912","company_id":"377b9ca2-ac79-48a5-8657-da630f9e447d","title":"AI Process Analyst","slug":"ai-process-analyst-b6f1a200","description":"About Netskope \n Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. \n \n Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive.     Visit us at  Netskope Careers. Please follow us on LinkedIn and Twitter @Netskope . \n \n About the position: \n The AI Process Analyst sits at the intersection of business strategy and emerging technology. In this role, you will partner with stakeholders across Marketing, Sales, Operations, Accounting, Finance, HR, and Support to deeply understand their objectives and reimagine existing workflows in an AI-native manner. Your goal is to move beyond incremental improvements, building unified, persona-based experiences consisting of AI-built applications and autonomous agents that leverage our core enterprise systems.\n Responsibilities: \n \n Strategic Partnership: Collaborate with business leads to identify pain points and document current-state processes with an eye for transformation.\n Workflow Reimagining:  Challenge the status quo by reimagining how work gets done when AI is the primary driver rather than an afterthought. \n Agent \u0026 App Development:  Build and deploy AI-driven applications and autonomous agents that consolidate fragmented tasks into a singular, persona-based experience.\n Systems Orchestration:  Ensure AI experiences effectively connect to and utilize our enterprise tech stack — specifically Salesforce, NetSuite, and Workday — as the primary Data of Record (DoR). \n Cross-Functional Translation:  Act as the bridge between technical possibilities and business realities, ensuring AI solutions provide tangible value and high adoption rates.\n AI \u0026 Agent Mastery:  Proficiency in prompting across various LLMs (e.g., OpenAI, Anthropic, Gemini) and a foundational understanding of AI agent development and orchestration.\n High Business Acumen:  Ability to quickly grasp diverse business models and identify specific opportunities where AI can move the needle.\n Ambiguity Architect:  You thrive in undefined environments. You possess a constant curiosity and a drive to learn through experimentation, iterative building, and navigating ambiguity without a map.\n Clear \u0026 Concise Communication:  Exceptional ability to write clearly and distill complex technical or process-driven concepts into simple, actionable insights.\n Human-Tech Intuition:  A deep understanding of the intersection of humanity and technology — ensuring tools are intuitive and enhance the human work experience.\n \n Requirements: \n \n 5 + years of experience in a role connecting business needs with technological solutions. We welcome candidates from either the technical or business side who demonstrate strong logical reasoning. \n Can provide specific examples of building and deploying AI-driven applications and autonomous agents that consolidate fragmented tasks into a singular, persona-based experience.\n A general understanding of how modern business systems work, including how data moves between objects and the basic logic of relational databases.\n A general understanding of enterprise platforms such as Salesforce, NetSuite, and Workday and their standard business workflows.\n An innate ability to see a list of manual steps and reimagine them as a seamless, automated flow.\n \n  Education: \n \n Bachelor’s degree preferred.  \n \n #LI-MD1 \n Compensation:  \n At Netskope, salary is one component of our competitive total rewards package. The salary range for this position is as listed below. This is a national range. For purposes of complying with applicable laws, the range applies to candidates in California, Colorado, Illinois, Maryland, New York, Washington, and other states. \n The successful candidate’s starting pay will also be determined based on job-related skills, experience, qualifications, location, and market conditions.  \n For all sales roles, the posted salary range is the On Target Earnings (OTE) range for the role, which is the sum of base salary and target commission amount at 100% goal achievement. \n In addition to salary, candidates may be eligible for other forms of compensation such as participation in a bonus plan (for non-sales roles) and a st","salary_min":85500,"salary_max":173000,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["agents","cloud","llm","fine-tuning"],"apply_url":"https://www.netskope.com/company/careers/open-positions/?gh_jid=8049641","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T23:06:34Z","expires_at":"2026-08-14T14:11:38.553449Z","created_at":"2026-07-09T14:09:34.601329Z","updated_at":"2026-07-15T14:11:38.676245Z","company_name":"Netskope","company_slug":"netskope","company_logo_url":"https://www.google.com/s2/favicons?domain=netskope.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1a986b20-b2ab-4938-b3d5-5fcbbdc73912"},{"id":"cc4472bd-80d6-4ce0-b4a1-abc0923120e0","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Staff Machine Learning Engineer, Ads Conversion Core Modeling","slug":"staff-machine-learning-engineer-ads-conversion-core-modeling-6958e589","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n We are looking for a Staff Machine Learning Engineer to lead the technical vision for our Ads Conversion Core Modeling team, building the state-of-the-art systems that power our global marketplace.\n  \n What you’ll do:  \n \n Lead the technical direction and development of state-of-the-art applied ML projects for ads conversion.  \n Design and build large-scale DNN models to improve user action prediction with low latency.  \n Mine text, visual, and user signals to better understand intention and infer interests from online activity.  \n Use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality.  \n Automate repeatable tasks such as documentation, reporting, and QA checks to speed up the development lifecycle.  \n Coach and mentor engineers while collaborating with product and sales to design new ad products.\n \n  \n What we’re looking for: \n \n Bachelor's degree in Computer Science, Statistics, or a related field.\n 6+ years of industry experience building production ML systems at scale (Search, Recommendations, or Ranking).  \n 2+ years of experience leading technical projects or teams.  \n Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.  \n Experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.\n Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.\n High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final deliverables.\n Strong mathematical foundation and experience with statistical methods and A/B testing. \n \n  \n Relocation Statement:  \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n  \n In-Office Requirement Statement: \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.\n This role will need to be in the office for in-person collaboration 1-2 times per month and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.\n \n #LI-HYBRID \n #LI-SM4\n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.\n Information regarding the culture at Pinterest and benefits available for this position can be found here . \n US based applicants only\n $222,716 — $389,753 USD \n Our Commitment to Inclusion: \n Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religiou","salary_min":222716,"salary_max":389753,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","code-generation","llm","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8011452","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T21:09:01Z","expires_at":"2026-08-14T14:10:33.648659Z","created_at":"2026-07-09T14:08:40.4464Z","updated_at":"2026-07-15T14:10:33.870462Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cc4472bd-80d6-4ce0-b4a1-abc0923120e0"},{"id":"90366268-3ef5-4d88-ab99-1047f2554463","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Chief Engineer, Advanced Effects","slug":"chief-engineer-advanced-effects-a77ce088","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 The Air Dominance and Strike (AD\u0026S) Chief Engineering Team is a driving force behind the technical execution and strategic vision of our most critical programs. They are responsible for architecting a vision for product development and guiding multi-disciplinary teams to deliver effectively. They are expected to own the mission and to be deeply involved in building the eco-system that enables execution. ABOUT THE JOB   You’ll own the technical development of large aircraft from white paper sketches and conceptual design through detailed design, build, flight test, transition to production, and sustainment. This includes vehicle layout and conceptual design, airframe and propulsion system design and integration, guidance section development, payload and datalink integration, fabrication and flight test. These projects will be diverse in nature and require you to leverage your technical expertise as well as leadership skills to set objectives, build a team, and drive to completion. The ability to leverage your intuition and prior experience in programmatic level decision will play a key component in making sure the right design/analysis/ and test steps are being completed to ensure success without simply completing steps for the sake of the process that don’t add value. The ideal candidate will leverage their experience executing and successfully completing prior highly optimized multi-disciplinary projects. WHAT YOU'LL DO: \n \n Lead technical and programmatic execution of new and existing air vehicle systems design, fabrication, test, productization and sustainment.\n Own the technical and programmatic success of your programs, establish technical and programmatic vision assemble teams of internal and external subject matter experts, and communicate that vision to them.\n Set up trades to enable the exploration of early conceptual designs while working closely with technical SME’s and Business Development teams to find the right solution to current and future gaps in the DOD capability to ensure the warfighter has the best solution for current and future conflicts.\n Manage the detailed design of the system and subsystems including requirements development, sub-system trades and optimization, risk management etc. to ensure the appropriate consideration of design key performance parameters, schedule, costs and risks.\n Coordinate the fabrication of prototype and low-rate production articles and subsystem/system level test efforts.\n Support remotely deployed operations of your systems.\n Work with senior leadership to ensure resource plans are adequate for work scope.\n \n REQUIRED QUALIFICATIONS: \n \n Deep understanding of unmanned aircraft at and above Group 3 class\n Bachelor’s degree in Aerospace, Mechanical, Electrical or Software engineering, or equivalent experience in a relevant field.\n Experience in a senior role leading air vehicle programs from initial concept through test and delivery to customers\n Experience driving strategic direction in competitive landscapes, solving complex system optimization challenges under tight constraints.\n Proven ability to deliver functional capabilities while aligning technical objectives with programmatic outcomes.\n Demonstrated collaboration and partnerships with internal and external stakeholders\n Strong understanding of the “why” behind Vehicle and Systems design.\n Experience working on mission critical DOD systems\n Experience troubleshooting and analyzing remotely deployed systems.\n Travel up to 50% to Customer and Test Sites\n Eligible to obtain and maintain an active U.S. Secret security clearance\n US Salary Range\n $220,000 — $292,000 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 (","salary_min":220000,"salary_max":292000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","computer-vision","payments","cloud"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/4742120007?gh_jid=4742120007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:52:15Z","expires_at":"2026-08-14T14:08:46.939766Z","created_at":"2026-07-09T14:07:00.202511Z","updated_at":"2026-07-15T14:08:47.073437Z","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/90366268-3ef5-4d88-ab99-1047f2554463"},{"id":"8e37b314-f237-44dc-a850-dd58524233c1","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Staff Data Scientist","slug":"staff-data-scientist-9bba8726","description":"Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.\n As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.  \n This role is for a current vacancy.\n A day in the life (Responsibilities) \n \n Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives.\n Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.\n Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.\n Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.\n Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.\n Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.\n Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.\n \n  \n What you'll need to thrive (Requirements) \n \n 5+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.\n Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.\n Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.\n Experience with distributed data processing and training, real-time inference, and ML Ops frameworks\n Prior experience mentoring other data scientists or acting as a tech lead.\n Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.\n Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).\n Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.\n Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.\n Excellent communication skills and the ability to influence both technical and non-technical stakeholders.\n Strong business acumen with the ability to align technical solutions with company goals.\n \n Bonus ingredients* : \n \n An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.\n Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.\n Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment.\n \n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n #LI-Remote\n The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. \n Pay Range \n $127,000 — $203,000 CAD \n How Toast Uses AI in its Hiring Process \n Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focus","salary_min":127000,"salary_max":203000,"location":"Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["tensorflow","reinforcement-learning","deep-learning","mlops","llm","pytorch","fine-tuning","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8052293","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:25:38Z","expires_at":"2026-08-14T14:11:50.57728Z","created_at":"2026-07-09T14:09:45.188959Z","updated_at":"2026-07-15T14:11:50.703686Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8e37b314-f237-44dc-a850-dd58524233c1"},{"id":"f04f6e13-ccf2-458b-8576-e7fa94481050","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Staff Data Scientist","slug":"staff-data-scientist-317fda4d","description":"Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.\n As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.\n A day in the life (Responsibilities) \n \n Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives.\n Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.\n Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.\n Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.\n Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.\n Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.\n Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.\n \n  \n What you'll need to thrive (Requirements) \n \n 7+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.\n Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.\n Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.\n Experience with distributed data processing and training, real-time inference, and ML Ops frameworks\n Prior experience mentoring other data scientists or acting as a tech lead.\n Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.\n Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).\n Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.\n Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.\n Excellent communication skills and the ability to influence both technical and non-technical stakeholders.\n Strong business acumen with the ability to align technical solutions with company goals.\n Experience building services on top of LLMs in a large scale production environment.\n \n Bonus ingredients* : \n \n An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.\n Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.\n Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment.\n \n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n #LI-Remote\n The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy . \n Zone A\n $170,000 — $272,000 USD \n Zone B\n $148,000 — $237,000 USD \n Zone C\n $133,000 — $213,000 USD \n How Toast Uses AI in its Hiring Process \n Throughout ","salary_min":133000,"salary_max":213000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["pytorch","tensorflow","reinforcement-learning","fine-tuning","deep-learning","mlops","llm","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8029049","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:23:10Z","expires_at":"2026-08-14T14:11:50.505714Z","created_at":"2026-07-09T14:09:45.268862Z","updated_at":"2026-07-15T14:11:50.63104Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f04f6e13-ccf2-458b-8576-e7fa94481050"},{"id":"eeeae1ee-77ec-47e2-8f3a-01c65044747d","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff Software Engineer, Labs: Applied AI","slug":"staff-software-engineer-labs-applied-ai-8a0854db","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 At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications.\n  \n Applied AI is one of the newest explorations within Anthropic Labs, the internal accelerator behind Claude Code, MCP, and Claude Design. Most of the world's work happens far from a code editor, and the people doing it have barely begun to feel what frontier AI can do. We believe Claude has a transformative role to play here — and we're at the earliest stage of exploring what that could look like. The engineers who join now will define where it goes.\n  \n We're looking for versatile, entrepreneurial engineers who are energized by building for users unlike themselves. In this role, you'll take frontier AI capabilities and turn them into applications that professionals in less software-native roles can pick up and trust — rapidly building and testing new experiences, partnering directly with researchers, domain experts, and users, and generating the insights that shape where this exploration goes next. You'll need to be comfortable with ambiguity, willing to kill your own projects when the data says to, and energized by the pace of building in uncharted territory.\n Responsibilities\n \n \n Rapidly prototype full-stack applications that bring frontier AI into workflows that have never been software-first, shipping early and often to maximize learning\n \n Immerse yourself in unfamiliar domains: sit with users, learn how their work actually gets done, and encode that understanding into products, evaluations, and workflows\n \n Collaborate closely with research teams to understand new model capabilities and translate them into tools that non-technical professionals reach for first\n \n Work directly with internal teams and external partners across industries to gather feedback, iterate quickly, and validate (or invalidate) product concepts\n \n Design and run structured experiments to test hypotheses, balancing creative exploration with rigorous evaluation\n \n Generate documentation and insights to guide successful prototypes toward full product teams\n \n Provide feedback to research teams about model effectiveness in real-world, domain-heavy settings and where capabilities can improve\n \n Flexibly contribute across Labs initiatives based on organizational priorities and emerging opportunities — context from one project should inform the next\n \n You may be a good fit if you\n \n \n Have 8+ years of experience building full-stack applications, with a track record of zero-to-one work in startup or startup-like environments\n \n Are deeply curious about how other industries work, and enjoy translating messy, real-world workflows into simple software\n \n Thrive in ambiguity and are energized (not anxious) by uncertainty — you're comfortable working on projects that might not exist in three months\n \n Have a hacker mentality: high agency, bias toward shipping, comfort with technical debt when it's the right tradeoff\n \n Are deeply user-centric — you validate ideas with actual users before over-investing and talk about problems before solutions\n \n Can articulate learnings from failed or killed projects without defensiveness; you treat your work as experiments\n \n Hold strong opinions loosely — you advocate forcefully for ideas but change your mind based on evidence\n \n Are a generalist who can transition between different problem spaces as priorities shift\n \n Work independently with good judgment about what matters, without needing constant direction\n \n Communicate effectively and can make complex AI capabilities feel intuitive to people who don't think in software\n \n Care about the societal impacts and ethics of your work\n \n Strong candidates may also have\n \n \n Experience building products for industries outside of tech — e.g., healthcare, manufacturing, logistics, construction, energy, agriculture, financial services, education, or the public sector\n \n A previous career, or deep hands-on exposure, in a field outside of software — you've been the user these products serve\n \n Background conducting embedded or field-based discovery: user research, interviews, ride-alongs, and usability testing with frontline professionals\n \n Experience integrating with the systems these industries actually run on (ERPs, EHRs, CRMs, dispatch, scheduling, or point-of-sale systems)\n \n Experience shipping software or AI applications to non-technical or frontline users — you know how to design for people wh","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","healthcare","fine-tuning","alignment"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5304425008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T19:55:29Z","expires_at":"2026-08-14T14:00:38.266563Z","created_at":"2026-07-09T14:00:41.408804Z","updated_at":"2026-07-15T14:00:38.403947Z","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/eeeae1ee-77ec-47e2-8f3a-01c65044747d"},{"id":"ffb8f345-cc3f-4a19-b74d-6117413ea12c","company_id":"3da82454-107f-427f-88e7-01f315ef93fb","title":"Member of Technical Staff - Training Platform","slug":"member-of-technical-staff-training-platform-bf6e9667","description":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\nROLE IMPACT\n\nYou'll help build our hosted training platform - the product that lets users launch LoRA and full fine-tuning runs on managed GPU clusters with a single API call or a few clicks. The role spans the developer-facing platform and the underlying Kubernetes-based training infrastructure that runs the jobs.\n\n\n\n\nCORE TECHNICAL RESPONSIBILITIES\n\n\n\n\nHOSTED TRAINING INFRASTRUCTURE\n\n - Design and operate Kubernetes-based training and inference orchestration across multi-cluster, multi-cloud GPU fleets\n\n - Build and maintain Helm charts that compose trainers, inference servers, environment servers, and supporting services into reproducible \"Training stacks\"\n\n - Develop the Python control-plane agents that watch pods, report run state to the platform, and keep clusters in sync\n\n - Implement scheduling and autoscaling for heterogeneous hardware (H100/H200/B200) using KEDA, LeaderWorkerSet, taints/tolerations, and gang scheduling\n\n - Run a tight GitOps workflow - every change ships through PRs, Helm values, and CI\n\n - Build node-local model caches, checkpoint pipelines, and shared storage for fast cold starts\n\n - Operate the observability stack (Prometheus, Grafana, Loki, DCGM) and make GPU cluster debugging fast\n\n\nPLATFORM DEVELOPMENT\n\n - Build the developer-facing surfaces for hosted training: job submission, live run monitoring, logs, metrics, model/adapter management, comparisons\n\n - Develop FastAPI backend services and REST APIs that bridge the platform to running clusters\n\n - Build real-time monitoring and debugging tools (streaming logs, step-level metrics, failure analysis)\n\n - Ship product UI in Next.js / React / TypeScript with shadcn, Tailwind, tRPC, and TanStack Query\n\n\nRESEARCH BRIDGE\n\n - Interface with the RL trainer, inference servers, and environment servers running inside our clusters\n\n - Productize new training capabilities (new model architectures, RL algorithms, modes)\n\n\n\n\n\nTECHNICAL REQUIREMENTS\n\nWe're looking for engineers who are fluent across three areas - you don't need to be the world's best at any one, but you should have real depth in all three and a clear point of view on how they connect.\n\n\n\n\nAI \u0026 GPU LANDSCAPE\n\n - Strong working knowledge of the modern AI stack - open model families, finetuning techniques (LoRA, QLoRA, full FT, RLHF/RLAIF), inference engines (vLLM, SGLang, TensorRT-LLM)\n\n - Familiarity with GPU hardware tradeoffs (H100 / H200 / B200, NVLink, interconnects, memory hierarchy) and what they mean for training and inference workloads\n\n - Understanding of distributed training fundamentals (data/tensor/pipeline/expert parallelism, NCCL, multi-node scheduling)\n\n - Awareness of what's happening at the frontier - new models, training methods, infra patterns - and the ability to translate that into product decisions\n   \n   \n\n\nKUBERNETES \u0026 INFRASTRUCTURE\n\n - Strong Kubernetes operations experience - Helm, CRDs, operators, KEDA, gang scheduling, GPU operator\n\n - Comfortable debugging real production clusters (kubectl, pod lifecycle, node issues, networking)\n\n - Cloud platform experience (GCP preferred - GCS, GKE, Cloud Run, Cloud Tasks)\n\n - Infrastructure automation (Helm, Terraform, Ansible) and a GitOps mindset\n\n - Observability: Prometheus, Grafana, Loki, OpenTelemetry, DCGM\n\n - Linux fundamentals: networking, namespaces, performance tuning\n   \n   \n\n\nPROGRAMMING \u0026 PLATFORM\n\n - Strong Python backend development (FastAPI, async, SQLAlchemy)\n\n - Comfortable building Python contr","salary_min":150000,"salary_max":300000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["gpu","cloud","fine-tuning","api-design","reinforcement-learning","distributed-systems","agents","llm"],"apply_url":"https://jobs.ashbyhq.com/PrimeIntellect/8706578d-5a01-4270-9d43-ed9cd998a982/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T18:45:47.645Z","expires_at":"2026-08-14T14:12:07.165126Z","created_at":"2026-05-11T14:11:38.576943Z","updated_at":"2026-07-15T14:12:07.28928Z","company_name":"Prime Intellect","company_slug":"PrimeIntellect","company_logo_url":"https://www.google.com/s2/favicons?domain=primeintellect.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ffb8f345-cc3f-4a19-b74d-6117413ea12c"},{"id":"5b4c2841-d819-4ab1-87e4-988c9bff0235","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Software Engineer, Identity","slug":"senior-software-engineer-identity-542360e2","description":"Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.\n At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.\n At the foundation of these products is the Identity  Engineering team.  In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.\n You will:\n \n Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems.\n Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect).\n Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access control (RBAC).\n Build software-defined identity governance policies to ensure compliance with security policies, industry regulations (e.g., NIST, SOC2, ISO 27001), and organizational standards.\n Present technical information to teams and stakeholders, providing guidance and insight on identity management and best practices.\n \n Ideally you’d have:\n \n 5+ years of full-time engineering experience, post-graduation with specialities in infrastructure and identity systems.\n Infrastructure expertise – IAM controls, Infrastructure as Code (Terraform, Pulumi), microservice deployment best practices.\n Hands-on experience working with OpenFGA, Authzed, Cedar, Topaz, or similar authorization frameworks at scale.\n Strong understanding of Zanzibar-based ReBAC models, relationship tuples, and access control evaluation.\n Strong knowledge of authentication standards such as OAuth 2.0, OIDC, SAML, and JWT, as well as industry standard IdP solutions like EntraID, Okta, etc.\n Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).\n Show a track record of independent ownership of successful engineering projects.\n Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.\n \n Nice to haves:\n \n Experience securing API access and implementing access control mechanisms at the application level.\n Multi-cloud infrastructure experience – AWS, Azure, GCP, and more.\n Proficiency in integrating IAM solutions with applications built using frameworks such as Java, Python, Node.js, or .NET.\n Mentorship/leadership experience supporting junior engineers\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, Seat","salary_min":216000,"salary_max":270000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","distributed-systems","generative-ai","cloud","llm","microservices","reinforcement-learning","pre-training"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4711898005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T18:08:31Z","expires_at":"2026-08-14T14:01:47.642927Z","created_at":"2026-07-09T14:01:29.84661Z","updated_at":"2026-07-15T14:01:47.810315Z","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/5b4c2841-d819-4ab1-87e4-988c9bff0235"}],"market_demand_pack":{"amount_cents":2900,"api_checkout_url":"https://aidevboard.com/api/v1/checkout?product_id=aidevboard_ai_skills_demand_pack","checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","currency":"USD","description":"Full ranked public AI/ML demand CSV, source job URLs, and decision brief with market and offer angles.","fulfillment":"automatic_email_after_paid_checkout","human_checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","name":"AI Market Demand Pack","next_step":"Open checkout_url for Stripe Checkout, or call api_checkout_url to get the non-charging checkout handoff payload.","price_usd":29,"product_id":"aidevboard_ai_skills_demand_pack","quote_url":"https://aidevboard.com/api/v1/quote?product_id=aidevboard_ai_skills_demand_pack"},"page":1,"per_page":20,"total":823,"total_pages":42}