{"id":129560,"url":"https://alion.io/job/uber-sr-staff-ml-engineer-applied-ai","title":"Sr Staff ML Engineer - Applied AI","company":{"id":230,"name":"Uber","domain":"uber.com","url":"https://alion.io/company/uber","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":92,"open_postings":132,"ghost_share":0,"stale_share":0.477,"repost_share":0.061,"time_to_fill_p50_days":8,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":267000,"max":297000,"currency":"USD","period":"year","gross":null,"usd_annual":297000},"salary_estimate":null,"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Computer Vision","optional":false},{"name":"LLM","optional":false},{"name":"PyTorch","optional":false}],"status":"live","first_seen_at":"2026-06-19T00:00:00Z","employer_posted_date":"2026-06-19","last_verified_at":"2026-10-20T18:56:57Z","board_verified":true,"closed_at":null,"days_open":123,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":123},"description":"About the Team\nThe Applied AI team collaborates with product teams across Uber to deliver innovative AI solutions for core business problems. We work closely with engineering, product and data science teams to understand core business problems and the potential for AI solutions, then deliver those AI solutions end-to-end. Key areas of expertise include Personalization, Generative AI, Computer Vision, ML Optimization, Geospatial AI.\nAbout the Role\nWe are building AI-native discovery experiences across Mobility and Delivery. Search, recommendations, and conversational AI are central to how millions of users discover rides, restaurants, grocery items, and retail products every day. We are hiring a Senior Staff ML Engineer to define the multi-year technical vision and architecture for foundation models powering these experiences.\nThe Uber Foundation Model would serve as the common semantic backbone that enables Uber to understand users, places, merchants, items, and behavioral patterns in a unified way. By building a shared representation layer and continuously improving it with cross-LOB signals, Uber ensures that intelligence compounds rather than fragments. This foundation powers personalization, search, agents, automation, and decision systems across Mobility, Delivery, and future surfaces.\nAt this level, you will set the long-term technical direction for the organization, drive alignment on product and engineering strategy at the executive level, and deliver step-change measurable impact at global scale.\nWhat the Candidate Will Do:\nDefine and champion the multi-year technical vision and architecture for foundation models across Search, Recommendations, and Conversational AI.\nSet the architectural standard and drive system design for critical, high-leverage ML platforms across Mobility and Delivery.\nLead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants, resolving complex technical trade-offs across organizational boundaries.\nDefine long-term investment areas (build vs fine-tune vs partner models) with clear business rationale and long-term viability.\nProvide principal-level technical leadership, mentoring Staff and Senior Staff engineers, and setting the bar for technical excellence across the entire AI organization.\nBasic Qualifications:\nMasters degree or Ph.D in Computer Science, Engineering, Mathematics\n12+ years of ML experience, including significant work on large-scale deep learning systems.\nDemonstrated ownership of high-impact ML systems in search, recommendations, or conversational AI.\nDeep expertise in transformers, retrieval systems, ranking, and embedding architectures.\nStrong experience with PyTorch and distributed training.\nProven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level.\nStrong product intuition and ability to connect model improvements to business outcomes.\nPreferred Qualifications:\nTrack record of successfully launching multi-year, multi-org ML initiatives that drove step-change business outcomes.\nSuccessfully championed and driven the adoption of multi-year technical roadmaps across multiple large engineering organizations.\nElevated engineering standards through mentorship and technical leadership, establishing org-wide best practices.\n ~~ ~~ For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.\nYou will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. 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