{"id":54760,"url":"https://alion.io/job/thinking-machines-lab-research-engineer-infrastructure-training-systems","title":"Research Engineer, Infrastructure, Training Systems","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":"AI/ML","role_family":"AI/ML","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":350000,"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":"PyTorch","optional":false},{"name":"DeepSpeed","optional":true},{"name":"Megatron-LM","optional":true},{"name":"XLA","optional":true}],"status":"live","first_seen_at":"2026-08-04T17:06:42Z","employer_posted_date":"2026-08-04","last_verified_at":"2026-10-18T07:27:00Z","board_verified":true,"closed_at":null,"days_open":74,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":74},"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 for deployment and research. Your goal is to make experimentation and training at Thinking Machines fast and reliable to ensure our research teams can focus on science, not system bottlenecks.\nThis role is ideal for someone who blends deep systems and performance expertise with a curiosity for machine learning at scale. You’ll take ownership of the training stack end to end, ensuring every GPU cycle drives scientific progress.\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, implement, and optimize distributed training systems that scale across thousands of GPUs and nodes for large-scale training workloads.\n\nDevelop high-performance optimizations to maximize throughput and efficiency.\n\nDevelop reusable frameworks and libraries to improve training reproducibility, reliability, and scalability for new model architectures.\n\nEstablish standards for reliability, maintainability, and security, ensuring systems are robust under rapid iteration.\n\nCollaborate with researchers and engineers to build scalable infrastructure.\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:\nPast experience working on distributed training for the world’s largest models to make them stable, reliable, and performant.\n\nTrack record of improving research productivity through infrastructure design or process improvements.\n\nContributions to open-source ML infrastructure such as PyTorch, XLA, Megatron-LM, or DeepSpeed.\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 $350,000 - $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":4022,"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":"2026-08-04T17:06:42Z"}],"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":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":28}],"liveness":{"score":10,"band":"cold","label":"Long shot","p_open":1,"p_active":0.359,"p_room":0.28,"age_days":73,"expected_fill_days":29,"reasons":["conf:0","velocity","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":475000,"is_top_pay":true},"html_url":"https://alion.io/job/thinking-machines-lab-research-engineer-infrastructure-training-systems","json_url":"https://alion.io/job/thinking-machines-lab-research-engineer-infrastructure-training-systems.json","meta":{"generated_at":"2026-10-18T10:10:30Z","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":15136,"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":14382},"rest":"https://alion.io/mcp/rest/get_company?id=14382"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fthinking-machines-lab-research-engineer-infrastructure-training-systems"},{"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-research-engineer-infrastructure-training-systems"},{"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-research-engineer-infrastructure-training-systems"},{"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-research-engineer-infrastructure-training-systems\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fthinking-machines-lab-research-engineer-infrastructure-training-systems"}]}