{"id":25810,"url":"https://alion.io/job/liquidai-member-of-technical-staff-gpu-performance-engineer","title":"Member of Technical Staff - GPU Performance Engineer","company":{"id":14548,"name":"Liquid AI","domain":"liquid.ai","url":"https://alion.io/company/liquid-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":71,"open_postings":20,"ghost_share":0.4,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":80,"computed_at":"2026-11-04T06:34:25Z"}},"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":["San Francisco, United States","Boston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":203000,"max_usd":404000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":890},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"cuDNN","optional":false},{"name":"Post-training","optional":false},{"name":"PyTorch","optional":false},{"name":"CUTLASS","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2025-07-29T20:46:39Z","employer_posted_date":"2025-07-29","last_verified_at":"2026-11-04T20:33:14Z","board_verified":true,"closed_at":null,"days_open":463,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":462},"description":"About Liquid AI\nSpun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.\nThe Opportunity\nOur models and workflows require performance work that generic frameworks don’t solve. You’ll design and ship custom CUDA kernels, profile at the hardware level, and integrate research ideas into production code that delivers measurable speedups in real pipelines (training, post-training, and inference). Our team is small, fast-moving, and high-ownership. We're looking for someone who finds joy in memory hierarchies, tensor cores, and profiler output.\nWhile San Francisco and Boston are preferred, we are open to other locations.\nWhat We're Looking For\nWe need someone who:\nWorks profiler-first: You use tools like Nsight Systems / Nsight Compute to find bottlenecks, validate hypotheses, and iterate until improvements show up in end-to-end benchmarks.\n\nBridges theory and practice: You can translate ideas from papers into implementations that are robust, testable, and performant.\n\nExecutes independently: Given an ambiguous bottleneck, you can drive from profiling to kernel/integration changes to benchmarked results to maintained ownership.\n\nCares about the details: Memory hierarchy, occupancy, launch configs, tensor core utilization, bandwidth vs compute limits.\n\nThe Work\nWrite high-performance GPU kernels for our novel model architectures\n\nIntegrate kernels into PyTorch pipelines (custom ops, extensions, dispatch, benchmarking)\n\nProfile and optimize training and inference workflows to eliminate bottlenecks\n\nBuild correctness tests and numerics checks\n\nBuild/maintain performance benchmarks and guardrails to prevent regressions\n\nCollaborate closely with researchers to turn promising ideas into shipped speedups\n\nDesired Experience\nMust-have:\nAuthored custom CUDA kernels (not only calling cuDNN/cuBLAS)\n\nStrong understanding of GPU architecture and performance: memory hierarchy, warps, shared memory/register pressure, bandwidth vs compute limits\n\nProficiency with low-level profiling (Nsight Systems/Compute) and performance methodology\n\nStrong C/C++ skills\n\nNice-to-have:\nCUTLASS experience and tensor core utilization strategies\n\nTriton kernel experience and/or PyTorch custom op integration\n\nExperience building benchmark harnesses and perf regression tests\n\nWhat Success Looks Like (Year One)\nMeasurable improvement on at least one critical end-to-end pipeline (throughput and/or latency), validated by repeatable benchmarks\n\nAt least one research-driven technique shipped as a production kernel and maintained over time\n\nPerformance regressions are detectable early via benchmarks/guardrails, not discovered late\n\nWhat We Offer\nUnique challenges: Our architectural innovations and efficiency requirements offer unique optimization challenges. High ownership from day one.\n\nCompensation: Competitive base salary with equity in a unicorn-stage company\n\nHealth: We pay 100% of medical, dental, and vision premiums for employees and dependents\n\nFinancial: 401(k) matching up to 4% of base pay\n\nTime Off: Unlimited PTO plus company-wide Refill Days throughout the year","description_format":"text","description_chars":3434,"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","Unlimited PTO"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Edge AI","Foundation Models","AI Research Labs"],"lifecycle":[{"event":"open","at":"2025-07-29T20:46:39Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 6","filings_12m":6,"filings_prev_12m":2,"green_card_filings_12m":0,"median_offered_wage_usd":242500,"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":5}],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.3,"p_room":0.28,"age_days":462,"expected_fill_days":80,"reasons":["conf:0","ghost","win:tail","crowd:"],"computed_at":"2026-11-04T06:34:25Z"},"pay":null,"html_url":"https://alion.io/job/liquidai-member-of-technical-staff-gpu-performance-engineer","json_url":"https://alion.io/job/liquidai-member-of-technical-staff-gpu-performance-engineer.json","meta":{"generated_at":"2026-11-04T21:28:08Z","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":33312,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-05T00:00:00Z"}},"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":14548},"rest":"https://alion.io/mcp/rest/get_company?id=14548"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fliquidai-member-of-technical-staff-gpu-performance-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%2Fliquidai-member-of-technical-staff-gpu-performance-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%2Fliquidai-member-of-technical-staff-gpu-performance-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/liquidai-member-of-technical-staff-gpu-performance-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fliquidai-member-of-technical-staff-gpu-performance-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":25810}},{"tool":"search_jobs","arguments":{"company":"liquid.ai","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":25810},"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. Docs: https://alion.io/developers"}}