{"id":2051384,"url":"https://alion.io/job/thinking-machines-lab-rl-systems-infra","title":"RL Systems - Infra","company":{"id":14382,"name":"Thinking Machines Lab","domain":"thinkingmachines.ai","url":"https://alion.io/company/thinking-machines-lab","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":425000,"max":475000,"currency":"USD","period":"year","gross":null,"usd_annual":475000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"DPO","optional":true},{"name":"Grafana","optional":true},{"name":"Kubernetes","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"PPO","optional":true},{"name":"Prometheus","optional":true},{"name":"Reward Modeling","optional":true},{"name":"RLHF","optional":true},{"name":"SLURM","optional":true}],"status":"live","first_seen_at":"2026-10-07T21:35:42Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-13T14:52:13Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About Thinking Machines\nThe mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.\nAbout the Role\nWe’re looking for an infrastructure research engineer to design and build the core systems that enable scalable, efficient training of large models through reinforcement learning.\nThis role sits at the intersection of research and large-scale systems engineering: a builder who understands both the algorithms behind RL and the realities of distributed training and inference at scale. You’ll wear many hats, from optimizing rollout and reward pipelines to enhancing reliability, observability, and orchestration, collaborating closely with researchers and infra teams to make reinforcement learning stable, fast, and production-ready.\nNote: This is an \"evergreen role\" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.\nWhat You’ll Do\nDesign, build, and optimize the infrastructure that powers large-scale reinforcement learning and post-training workloads.\n\nImprove the reliability and scalability of RL training pipeline, distributed RL workloads, and training throughput.\n\nDevelop shared monitoring and observability tools to ensure high uptime, debuggability, and reproducibility for RL systems.\n\nCollaborate with researchers to translate algorithmic ideas into production-grade training pipelines.\n\nBuild evaluation and benchmarking infrastructure that measures model progress on helpfulness, safety, and factuality.\n\nPublish and share learnings through internal documentation, open-source libraries, or technical reports that advance the field of scalable AI infrastructure.\n\nSkills and Qualifications\nMinimum qualifications:\nBachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar.\n\nStrong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases\n\nUnderstanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures.\n\nThrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.\n\nA bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.\n\nPreferred qualifications - we encourage you to apply if you meet some but not all of these:\nExperience training or supporting large-scale language models with tens of billions of parameters or more.\n\nExperience working with reinforcement learning workloads (e.g., PPO, DPO, RLHF, or reward modeling).\n\nBackground in high-performance or reliability engineering - distributed training frameworks and cluster orchestration (Kubernetes, Slurm).\n\nFamiliarity with monitoring and observability tools (Prometheus, Grafana, OpenTelemetry).\n\nContributions to large-scale ML research or infrastructure, open-source frameworks, or internal performance optimization efforts.\n\nLogistics\nLocation: This role is based in San Francisco, California.\n\nCompensation: Depending on background, skills and experience, the expected annual salary range for this position is $425,000 - $475,000 USD.\n\nVisa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.\n\nBenefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.","description_format":"text","description_chars":4352,"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":["Parental leave","Unlimited PTO"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Multimodal AI","Foundation Models","AI Research Labs","AI Development Tools"],"lifecycle":[{"event":"open","at":"2026-10-07T21:57:22Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 30","filings_12m":30,"filings_prev_12m":8,"green_card_filings_12m":0,"median_offered_wage_usd":192500,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":7}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.902,"p_room":1,"age_days":5,"expected_fill_days":29,"reasons":["conf:1","velocity","win:early"],"computed_at":"2026-10-13T05:45:00Z"},"pay":{"stated_usd_annual":475000,"is_top_pay":true},"html_url":"https://alion.io/job/thinking-machines-lab-rl-systems-infra","json_url":"https://alion.io/job/thinking-machines-lab-rl-systems-infra.json","meta":{"generated_at":"2026-10-13T16:25:27Z","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":24971,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-14T00:00:00Z"}},"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":14382},"rest":"https://alion.io/mcp/rest/get_company?id=14382"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fthinking-machines-lab-rl-systems-infra"},{"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%2Fthinking-machines-lab-rl-systems-infra"},{"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%2Fthinking-machines-lab-rl-systems-infra"},{"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/thinking-machines-lab-rl-systems-infra\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fthinking-machines-lab-rl-systems-infra"}]}