{"id":1631535,"url":"https://alion.io/job/preferencemodel-member-of-technical-staff-research-engineer-post-training","title":"Member of Technical Staff - Research Engineer, Post-training","company":{"id":2542085,"name":"Preference Model","domain":"preferencemodel.com","url":"https://alion.io/company/preferencemodel","size_band":null,"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":"staff","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":350000,"currency":"USD","period":"year","gross":null,"usd_annual":350000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Anthropic","optional":false},{"name":"Claude","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false}],"status":"live","first_seen_at":"2026-09-11T23:24:44Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-28T23:24:40Z","board_verified":true,"closed_at":null,"days_open":47,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":47},"description":"About Us\nPreference Model is a superintelligence data research company. We build RL environments for training capable, better-aligned superintelligences.\nAlmost every aspect of how a model behaves is shaped by the reward signals it's trained on. The biggest problem with AIs today is that they don't always do what we intend. Sometimes that's because they aren't capable enough, and sometimes it's because they aren't aligned. Both problems come down to the training objectives.\nWe're trying to address both of these issues in the most direct, highest leverage way available to us, which today means researching how to build RL environments better, not just for the AIs of today but for the AIs as they will be when they outsmart us.\nOver the past year, we've built RL environments for several frontier labs, and we're backed by $16M in seed funding led by a16z. Our founding team has previous experience on Anthropic’s data team building data infrastructure, and datasets behind Claude.\nAbout the Role\nModels of the future will be able to train themselves on tasks that they are not good at. We are interested in investigating how far we can push the boundaries of self-directed learning. We are looking for machine learning Research Engineers or Research Scientists to push the frontier of post-training on large language models in a role that blends research and engineering, requiring you to implement novel approaches and shape research directions.\nWhat You Will Do:\nTrain and evaluate models on our proprietary RL environments to validate data quality, surface gaps in task coverage, and close the feedback loop between environment design and model capability.\n\nArchitect and optimize our RL training infrastructure, from training abstractions to distributed experiment management, using frameworks like Verl, OpenRLHF, or similar. Help scale our systems to handle increasingly complex research workflows.\n\nDesign, implement, and test training environments, evaluations, and methodologies for RL agents.\n\nProfile and optimize training runs end-to-end, from data loading through reward computation, to maximize experiment throughput and shorten the research iteration cycle.\n\nWhat We are Looking For\nIndustry experience running end-to-end LLM post-training pipelines of models sizes at least 7B in size\n\nProficiency in Python and PyTorch or JAX\n\nExperience with at least one modern RL training framework\n\nExperience building and operating ML infrastructure at scale\n\nYou may be a good fit if you also:\nHave experience evaluating model outputs and building reward or evaluation signals\n\nStay current on post-training research and can translate papers into running code\n\nHave strong opinions (loosely held) about how to structure RL training code for reproducibility and fast iteration\n\nCan balance research exploration with engineering rigor\n\nHave strong systems design and communication skills\n\nCandidates don't need a PhD or extensive publications. Some of the best researchers have no formal ML training and gained experience building industry products. We believe adaptability combined with exceptional communication and collaboration skills are the most important ingredients for successful startup research.\nWhat We Offer:\nCompetitive cash and equity compensation (>90th percentile)\n\nOwnership and autonomy in a fast moving startup environment\n\nOpportunity to work with top machine learning engineers\n\nHealth, vision, dental, benefits\n\n401K match\n\nLunch provided everyday onsite\n\nWeekly snack orders\n\nVisa sponsorship & relocation support available\n\nWe value diverse perspectives and experiences. If you're excited about this role but don't check every box, we still encourage you to apply.","description_format":"text","description_chars":3700,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Reinforcement Learning","AI Training Data & Annotation"],"lifecycle":[{"event":"open","at":"2026-10-01T21:23:08Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 1","filings_12m":1,"filings_prev_12m":0,"green_card_filings_12m":0,"median_offered_wage_usd":162500,"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":1}],"liveness":{"score":34,"band":"fade","label":"Fading","p_open":1,"p_active":0.618,"p_room":0.55,"age_days":46,"expected_fill_days":31,"reasons":["conf:0","win:tail"],"computed_at":"2026-10-28T05:59:10Z"},"pay":{"stated_usd_annual":350000,"is_top_pay":true},"html_url":"https://alion.io/job/preferencemodel-member-of-technical-staff-research-engineer-post-training","json_url":"https://alion.io/job/preferencemodel-member-of-technical-staff-research-engineer-post-training.json","meta":{"generated_at":"2026-10-29T01:44:01Z","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":2624,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-30T00:00:00Z"}},"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":2542085},"rest":"https://alion.io/mcp/rest/get_company?id=2542085"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpreferencemodel-member-of-technical-staff-research-engineer-post-training"},{"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%2Fpreferencemodel-member-of-technical-staff-research-engineer-post-training"},{"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%2Fpreferencemodel-member-of-technical-staff-research-engineer-post-training"},{"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/preferencemodel-member-of-technical-staff-research-engineer-post-training\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpreferencemodel-member-of-technical-staff-research-engineer-post-training"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":1631535}},{"tool":"search_jobs","arguments":{"company":"preferencemodel.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":1631535},"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"}}