{"id":11434,"url":"https://alion.io/job/reducto-machine-learning-infrastructure-tech-lead","title":"Machine Learning Infrastructure Tech Lead","company":{"id":3678,"name":"Reducto","domain":"reducto.ai","url":"https://alion.io/company/reducto","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":88,"open_postings":33,"ghost_share":0,"stale_share":0.273,"repost_share":0,"time_to_fill_p50_days":85,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","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":200000,"max":325000,"currency":"USD","period":"year","gross":null,"usd_annual":325000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Kubernetes","optional":false},{"name":"Python","optional":false},{"name":"CUDA","optional":true},{"name":"CUDA Toolkit","optional":true},{"name":"PyTorch","optional":true},{"name":"Ray","optional":true},{"name":"SGLang","optional":true},{"name":"TensorRT","optional":true},{"name":"TensorRT-LLM","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-07-16T20:47:20Z","employer_posted_date":"2026-07-16","last_verified_at":"2026-10-18T08:57:22Z","board_verified":true,"closed_at":null,"days_open":93,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":93},"description":"About Reducto\nReducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows.\nWe’ve grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms.\nReducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital.\nThe Opportunity\nAs our ML Infrastructure Tech Lead, you'll own the systems that make high-performance model training and inference possible at Reducto.\nThis is a deeply hands-on role: roughly 80% of your time will be spent building, debugging, and optimizing our infrastructure. The remaining 20% will focus on setting technical direction - identifying bottlenecks, planning our infrastructure roadmap, and helping the ML and Platform teams make strong architectural decisions.\nYou'll work across the stack, from model-serving kernels and GPU utilization to distributed systems and Kubernetes. We're looking for someone with the experience and judgment to lead ambiguous, high-impact infrastructure projects while remaining close to the code.\nThis is a fully in-person role at our San Francisco office.\nWhat You'll Do\nOwn the technical direction and roadmap for Reducto's ML infrastructure.\n\nBuild and maintain our training and inference stack, balancing fast experimentation with high-performance production serving.\n\nOptimize model serving at every layer, including kernels, runtimes, batching, scheduling, and distributed inference.\n\nDesign systems for reliable multi-node, multi-GPU training and inference.\n\nImprove GPU utilization, latency, throughput, reliability, observability, and cost efficiency.\n\nDevelop benchmarks that identify bottlenecks and guide infrastructure investments.\n\nEvaluate state-of-the-art advances in training and inference and apply the ones that matter.\n\nBuild the tooling and abstractions that help ML engineers move quickly from experiments to production.\n\nPartner with ML and Platform engineers on architecture, capacity planning, and technical prioritization.\n\nRaise the engineering bar through design reviews, mentorship, and hands-on technical leadership.\n\nYou'll Thrive Here If You\nHave 5+ years of experience building production infrastructure, including significant ML systems experience.\n\nHave led complex technical projects from an ambiguous problem through production deployment.\n\nAre equally comfortable setting direction and personally implementing the hardest parts.\n\nHave strong Python and systems-engineering skills.\n\nUnderstand the performance characteristics of modern GPU training or inference workloads.\n\nAre comfortable with Kubernetes and distributed training or serving frameworks.\n\nCan reason across low-level model performance and higher-level platform architecture.\n\nHold yourself to a high bar for quality, precision, and operational reliability.\n\nOperate well in a fast-changing, high-growth environment.\n\nTake full ownership from strategy through execution.\n\nBonus Points If You\nHave optimized or implemented CUDA, Triton, or custom model-serving kernels.\n\nHave contributed meaningfully to frameworks such as vLLM, SGLang, PyTorch, TensorRT-LLM, Ray, or related open-source systems.\n\nHave operated distributed inference or training across hundreds or thousands of GPUs.\n\nHave built observability, scheduling, or capacity-management systems for GPU workloads.\n\nHave experience at an early-stage or high-growth startup.\n\nCare deeply about connecting technical excellence to measurable business impact.\n\nWhy Reducto\nImpact: Your work directly shapes how the world’s best AI companies access and use enterprise data.\n\nSpeed: We move fast, ship often, and iterate in days, not months.\n\nLearning: Work alongside world-class engineers, operators, and founders who care deeply about product, precision, and velocity.\n\nBenefits\nUnlimited PTO, because great work requires recharging.\n\nDaily Lunch, enjoy free lunch with teammates in the office.\n\nCommuter Reimbursement, we’ll cover your transportation costs.\n\nComprehensive Insurance, medical, dental, and vision.\n\nHealth and Wellness Budget, up to $150 per month for wellness spending such as gym memberships or fitness classes.\n\nParental Leave, flexible scheduling that works for you and your family.Working at Reducto\n\nThis is an in-person role at our San Francisco office. We're an early-stage company, which means the role requires working hard and moving quickly. Please only apply if that excites you.\nEqual Opportunity\n Reducto is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration without regard to sex, race, color, age, national origin, religion, disability, sexual orientation, gender identity, veteran status, or any other protected category.","description_format":"text","description_chars":5076,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Gym membership","Parental leave","Unlimited PTO"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Machine Learning","Custom Software Development","AI Development Tools","Document AI"],"lifecycle":[{"event":"open","at":"2026-07-16T20:47:20Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 4","filings_12m":4,"filings_prev_12m":0,"green_card_filings_12m":0,"median_offered_wage_usd":217500,"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":4}],"liveness":{"score":33,"band":"fade","label":"Fading","p_open":1,"p_active":0.741,"p_room":0.44,"age_days":92,"expected_fill_days":85,"reasons":["conf:2","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":325000,"is_top_pay":true},"html_url":"https://alion.io/job/reducto-machine-learning-infrastructure-tech-lead","json_url":"https://alion.io/job/reducto-machine-learning-infrastructure-tech-lead.json","meta":{"generated_at":"2026-10-18T09:53:34Z","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":14619,"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":3678},"rest":"https://alion.io/mcp/rest/get_company?id=3678"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Freducto-machine-learning-infrastructure-tech-lead"},{"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%2Freducto-machine-learning-infrastructure-tech-lead"},{"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%2Freducto-machine-learning-infrastructure-tech-lead"},{"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/reducto-machine-learning-infrastructure-tech-lead\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Freducto-machine-learning-infrastructure-tech-lead"}]}