{"id":1281865,"url":"https://alion.io/job/hud-research-manager","title":"Senior Research Manager","company":{"id":678875,"name":"HUD","domain":"hud.so","url":"https://alion.io/company/hud-3","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":3,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-02T05:45:00Z"}},"role":"Science & Research","role_family":"Science & Research","seniority":"senior","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","Singapore"],"countries":["US","SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":295000,"currency":"USD","period":"year","gross":null,"usd_annual":295000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ChatGPT","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Machine Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Synthetic Data","optional":false}],"status":"live","first_seen_at":"2026-09-26T01:03:40Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-10-02T18:46:00Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"About HUD\nHUD 's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs.\nAbout the role\nWe’re looking for a Research Manager to lead research that makes HUD’s agent training data and evals more useful for improving frontier models. You’ll lead research engineers through ambiguous projects, and turn findings into methods that can be used at scale.\nYou’ll stay close to the technical work while helping the team choose the right questions, run rigorous experiments, and deliver results. This role calls for an understanding of how and why models train: which signals teach useful behavior, where apparent progress is misleading, and how data and eval design can change outcomes.\nResponsibilities\nSet the research direction for data quality, including how HUD measures how training data impacts agent behavior and performance after training, and what makes data valuable\n\nLead synthetic data efforts to understand how various data types can be efficiently transformed into formats useful for training\n\nLead research engineers from problem definition through experiments, implementation, and clear conclusions; coach them to strengthen technical judgment and execution\n\nDesign and review experiments that connect model behavior and failure modes to data, environment, and reward design\n\nDevelop methods for validating and improving training data at scale, including trajectory audits, adversarial checks, and feedback loops that help users improve their data\n\nPartner with research engineers, domain experts, and data vendors to turn research insights into better workflows, tools, and quality standards\n\nCommunicate findings and tradeoffs clearly so the team can prioritize work and apply what it learns across research areas\n\nExperience\nYou may be a good fit if you have:\nExperience leading technical research projects to completion, from an open question to evidence, a decision, and a working result\n\nExperience directly managing and mentoring researchers or research engineers while remaining engaged in technical work\n\nA strong understanding of machine learning and reinforcement learning, including how training objectives, data, and feedback shape model behavior\n\nExperience with agent training data, evals, benchmarks, synthetic data, or model evaluation infrastructure\n\nSound experimental judgment: you can distinguish a useful training signal from a task or metric that only looks convincing\n\nStrong written communication and the ability to explain methods and findings to researchers, engineers, and external partners\n\nStrong candidates may also have:\nBuilt scalable data quality systems or validation pipelines for model training\n\nExperience diagnosing reward hacking, grader errors, or other subtle agent failure modes\n\nExperience translating research findings into tools and processes used by others\n\nEarly-stage startup experience and strong communication skills for collaboration across teams and time zones\n\nWe prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria.\nTeam & company details\nTeam Size: ~25 people currently, mostly full-time in-person, but some remote.\n\nOur team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc.\n\nCompany stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand.\n\nLogistics\nEmployment: Full-time.\n\nLocation: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones.\n\nVisa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore.\n\nTimeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial.\n\nWhat we offer\nCompetitive compensation\n\n100% covered top-of-the-line medical, dental, and vision from Blue Shield of CA (US employees)\n\nLunch and dinner when you’re in the office (in-office employees)\n\nCompany-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays\n\nOther perks including an Equinox membership, 401k, and commuter benefits (US employees)\n\nUnlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is.\n\nCompensation\nActual offers are adjusted for experience and location, but our base salary bands are\nSan Francisco (and other major US cities): $200,000 - $295,000\n\nSingapore: $150,000 - $225,000\n\nRest of world: $120,000 - $225,000\n\nDue to high volume, we may not actively respond to every application, but feel free to contact us at  or elsewhere if we missed your application!","description_format":"text","description_chars":5256,"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":["401k plan"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-26T02:56:57Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.898,"p_room":1,"age_days":6,"expected_fill_days":35,"reasons":["conf:11","velocity","win:early"],"computed_at":"2026-10-02T05:45:00Z"},"pay":{"stated_usd_annual":295000,"is_top_pay":true},"html_url":"https://alion.io/job/hud-research-manager","json_url":"https://alion.io/job/hud-research-manager.json","meta":{"generated_at":"2026-10-03T03:34:24Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3466,"day_limit":5000,"remaining_today":1534,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}