{"id":146672,"url":"https://alion.io/job/river-ai-member-of-program-staff-data","title":"Member of Program Staff, Data","company":{"id":25477,"name":"River AI","domain":"river.ai","url":"https://alion.io/company/river-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":67,"open_postings":18,"ghost_share":0.556,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-27T05:46:45Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Post-training","optional":false},{"name":"Function Calling","optional":true},{"name":"LLM","optional":true},{"name":"Pre-training","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"SFT","optional":true}],"status":"live","first_seen_at":"2026-06-12T22:01:40Z","employer_posted_date":"2026-09-20","last_verified_at":"2026-10-27T02:42:11Z","board_verified":true,"closed_at":null,"days_open":136,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":136},"description":"At River, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, bespoke training infrastructure, next-generation UIs, and frontier deep learning research.\nWho we are\nWe are scientists, engineers, and builders from the industry's top tech companies and AI labs. We bring a proven track record of scaling consumer systems for hundreds of millions of users and architecting the pre-training infrastructure behind today's frontier models.\nAbout the Role\nWe are looking for exceptional people to oversee our data efforts. Your main goal is to design and run data campaigns and evaluations for next-generation models and personalization systems. You will also play a significant role in crafting our training recipes and interfaces for tutors & users.\nWhat You’ll Do\nBuild & oversee the data campaigns that feed training pipelines for next-generation agents and personalization systems. You will work closely with our research teams to figure out what data is needed.\nCreate evaluations for general capabilities, model behavior, continual learning, personalization.\nArchitect and deploy new clients & interfaces for collecting feedback from tutors and users, working closely with both product and research team members.\nManage external partnerships with data labelers on a variety of campaigns.\nSkills & Qualifications\nMinimum Qualifications:\nCompleted or in-progress Bachelors or higher degree, or equivalent professional experience.\nExtensive experience running large-scale data campaigns or post-training at frontier AI company or research institution.\nExceptional oral and written communication skills.\nOperational experience with hiring or managing human data labelers.\nEvidence of expertise / top of field in a non-technical domain, such as but not limited to: literature, philosophy, history, economics, sociology, psychology, political science.\nA highly collaborative mindset and a bias for action to push boundaries in a fast-paced environment.\nPreferred Qualifications: (We encourage you to apply even if you don't meet all of these)\nBA, Masters, or Ph.D. in a humanities, social science, or STEM.\nExperience with managing external partnerships and contracts.\nExceptional product judgment with the ability to reason backward from user needs, alongside a high degree of ownership to navigate ambiguity.\nHands-on experience with LLM systems, including APIs, agents, tool calling, prompt iteration, eval frameworks, and inference constraints.\nFamiliarity with modern deep learning algorithms including reinforcement learning, supervised fine-tuning.\nLogistics & Benefits\nLocation: Palo Alto, California.\nCompensation: Depending on experience and skills the expected base pay is $200,000 - $300,000 USD per year, plus equity.\nBenefits: Comprehensive health, dental, and vision insurance; 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