{"id":1869812,"url":"https://alion.io/job/people-in-ai-staff-machine-learning-engineer","title":"Staff Machine Learning Engineer","company":{"id":3862080,"name":"People In AI","domain":"peopleinai.com","url":"https://alion.io/company/people-in-ai","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":75,"open_postings":14,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":265000,"max":280000,"currency":"USD","period":"year","gross":null,"usd_annual":280000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"DPO","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GRPO","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Post-training","optional":false},{"name":"PPO","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"SFT","optional":false}],"status":"live","first_seen_at":"2026-08-26T00:00:00Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-18T10:19:17Z","board_verified":true,"closed_at":null,"days_open":53,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":53},"description":"Staff Machine Learning Engineer $265,000 - $280,000 Base Salary + Equity Location: San Francisco - hybrid, 3 days per week in office\nThe Company\nA fast-growing AI technology company is expanding its Machine Learning team in San Francisco.\nThe business builds advanced systems used to train, evaluate, and improve modern AI models. Its work spans reinforcement learning, post-training, model evaluation, agentic systems, and the infrastructure required to support increasingly sophisticated AI capabilities.\nThe engineering environment is highly technical and moves quickly, with a strong emphasis on ownership, judgment, experimentation, and execution.\nThe Opportunity\nThis is a Staff-level Machine Learning Engineering role sitting between research engineering and production ML infrastructure.\nYou will work on technical problems involving reinforcement learning, model post-training, agent training, evaluation, and the systems required to run these workflows reliably at scale.\nThis is not an application-layer role focused primarily on integrating third-party LLM APIs. The work sits closer to the underlying models, training signals, environments, evaluation methodologies, and infrastructure that determine whether AI systems actually improve.\nThe Role\nYou will combine hands-on Machine Learning Engineering with Staff-level technical leadership.\nThe role is highly dynamic. Depending on the project, you could be running post-training experiments, designing evaluation systems, building ML infrastructure, defining technical architecture, or leading a small group of engineers through an ambiguous technical problem.\nThe team already has strong implementers. This hire is intended to add another level of technical judgment and direction, helping determine what should be built, how it should be designed, and how the team should execute.\nWhat You’ll Do\nDesign and build reinforcement learning environments for agentic tasks.\n\nDevelop task definitions, tool interfaces, state management, reward structures, and evaluation logic.\n\nBuild systems capable of running large numbers of agent trajectories and experiments in parallel.\n\nDevelop verifiers, graders, rubrics, and other approaches for evaluating open-ended model behavior.\n\nBuild fine-tuning and post-training pipelines spanning supervised fine-tuning and reinforcement learning.\n\nRun ML experiments and diagnose model behavior, training performance, reward quality, and data quality.\n\nBuild scalable evaluation systems used to measure model and agent performance.\n\nDevelop production-grade ML infrastructure, including orchestration, reliability, fault tolerance, and experiment management.\n\nTranslate ambiguous technical problems into clear architectures and execution plans.\n\nProvide technical leadership to other engineers while remaining deeply hands-on.\n\nUse modern AI development and coding tools while maintaining strong engineering judgment around the systems they produce.\n\nWhat You’ll Bring\nStrong hands-on Machine Learning Engineering experience with meaningful depth beyond model deployment or API integration.\n\nPractical experience with model fine-tuning or post-training.\n\nExposure to supervised fine-tuning and reinforcement learning or preference-optimization techniques such as GRPO, PPO, DPO, or similar.\n\nExperience with agentic systems, model evaluation, training environments, reward design, or closely related areas.\n\nStrong understanding of how to determine whether a model is improving and how to diagnose unsuccessful training runs.\n\nStrong Python skills and excellent production software engineering fundamentals.\n\nExperience with system design, distributed systems, ML infrastructure, platform engineering, or data systems.\n\nStrong architectural judgment and the ability to make and defend difficult technical decisions.\n\nExperience providing technical direction to other engineers without relying on formal management authority.\n\nHigh agency and a track record of identifying important problems independently and driving them through to completion.\n\nComfort working in ambiguous, rapidly changing environments.\n\nStrong communication skills and the ability to collaborate with highly technical stakeholders.\n\nWhat This Role Requires\nGenuine hands-on Machine Learning experience rather than solely software engineering around ML products.\n\nStrong understanding of modern model training, evaluation, and agent development.\n\nAbility to operate at Staff level by setting technical direction, not simply executing against predefined requirements.\n\nStrong production engineering fundamentals alongside ML depth.\n\nComfort moving between experimentation, infrastructure, architecture, and implementation.\n\nAbility to influence and lead technically without requiring formal authority.\n\nA strong builder mindset rather than a purely academic or publication-oriented background.\n\nComfort using AI coding tools as part of day-to-day engineering while fully understanding and defending the resulting implementation.\n\nWhy Join\nWork on reinforcement learning, agent training, post-training, evaluation, and other technically challenging areas of modern AI.\n\nOperate closer to the underlying models and training systems rather than focusing primarily on application-layer integrations.\n\nCombine deep ML problems with production engineering responsibility.\n\nTake meaningful technical ownership while remaining hands-on.\n\nWork across a range of fast-moving AI problems rather than becoming narrowly siloed into a single technical area.\n\nJoin an environment that values speed, high agency, strong engineering judgment, and individual impact.\n\nAbout People in AI\nPeople in AI is a specialist recruitment partner connecting exceptional AI, machine learning, data, and engineering talent with some of the most ambitious technology companies in the world. We work closely with founders, technical leaders, and hiring teams to represent opportunities accurately and help candidates assess genuine fit.","description_format":"text","description_chars":5969,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-04T21:13:54Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.247,"p_room":0.45,"age_days":52,"expected_fill_days":30,"reasons":["conf:4","agency","stale_co","velocity","win:tail"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":280000,"is_top_pay":false},"html_url":"https://alion.io/job/people-in-ai-staff-machine-learning-engineer","json_url":"https://alion.io/job/people-in-ai-staff-machine-learning-engineer.json","meta":{"generated_at":"2026-10-18T11:42:57Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":17414,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-19T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":3862080},"rest":"https://alion.io/mcp/rest/get_company?id=3862080"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpeople-in-ai-staff-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpeople-in-ai-staff-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpeople-in-ai-staff-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/people-in-ai-staff-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpeople-in-ai-staff-machine-learning-engineer"}]}