{"id":54759,"url":"https://alion.io/job/thinking-machines-lab-research-engineer-infrastructure-kernels","title":"Research Engineer, Infrastructure, Kernels","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":{"grade":"B","score":75,"open_postings":20,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-11-05T05:54:30Z"}},"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":"CUDA","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"PyTorch","optional":false},{"name":"Triton","optional":false},{"name":"Apache TVM","optional":true},{"name":"XLA","optional":true}],"status":"live","first_seen_at":"2026-08-04T17:26:20Z","employer_posted_date":"2026-08-04","last_verified_at":"2026-11-05T04:21:21Z","board_verified":true,"closed_at":null,"days_open":92,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":92},"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, optimize, and maintain the compute foundations that power large-scale language model training. You will develop high-performance ML kernels (e.g., CUDA, CuTe, Triton), enable efficient low-precision arithmetic, and improve the distributed compute stack that makes training large models possible.\nThis role is perfect for an engineer who enjoys working close to the metal and across the research boundary. You’ll collaborate with researchers and systems architects to bridge algorithmic design with hardware efficiency. You’ll prototype new kernel implementations, profile performance across hardware generations, and help define the numerical and parallelism strategies that determine how we scale next-generation AI systems.\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 and implement custom ML kernels (e.g., CUDA, CuTe, Triton) for core LLM operations such as attention, matrix multiplication, gating, and normalization, optimized for modern GPU and accelerator architectures.\n\nDesign and think through compute primitives to reduce memory bandwidth bottlenecks and improve kernel compute efficiency.\n\nCollaborate with research teams to align kernel-level optimizations with model architecture and algorithmic goals.\n\nDevelop and maintain a library of reusable kernels and performance benchmarks that serve as the foundation for internal model training.\n\nContribute to infrastructure stability and scalability, ensuring reproducibility, consistency across precision formats, and high utilization of compute resources.\n\nDocument and share insights through internal talks, technical papers, or open-source contributions to strengthen the broader ML systems community.\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\nProficiency in CUDA, CuTe, Triton, or other GPU programming frameworks.\n\nDemonstrated ability to analyze, profile, and optimize compute-intensive workloads.\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\nTrack record of improving research productivity through infrastructure design or process improvements.\n\nExperience developing or tuning kernels for deep learning frameworks such as PyTorch, JAX, or custom accelerators.\n\nFamiliarity with tensor parallelism, pipeline parallelism, or distributed data processing frameworks.\n\nExperience implementing low-precision formats (FP8, INT8, block floating point) or contributing to related compiler stacks (e.g., XLA, TVM).\n\nContributions to open-source GPU, ML systems, or compiler optimization projects.\n\nPrior research or engineering experience in numerical optimization, communication-efficient training, or scalable AI infrastructure.\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":5039,"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":"2026-08-04T17:26:20Z"}],"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":"2026-10-29T16:27:21+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":28}],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.277,"p_room":0.28,"age_days":92,"expected_fill_days":29,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:"],"computed_at":"2026-11-05T05:54:30Z"},"pay":{"stated_usd_annual":475000,"is_top_pay":true},"html_url":"https://alion.io/job/thinking-machines-lab-research-engineer-infrastructure-kernels","json_url":"https://alion.io/job/thinking-machines-lab-research-engineer-infrastructure-kernels.json","meta":{"generated_at":"2026-11-05T09:02:05Z","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":11419,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-06T00:00:00Z"}},"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-kernels"},{"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-kernels"},{"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-kernels"},{"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-kernels\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fthinking-machines-lab-research-engineer-infrastructure-kernels"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":54759}},{"tool":"search_jobs","arguments":{"company":"thinkingmachines.ai","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":54759},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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