About the Team
The 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.
About the Role
We 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.
The 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.
At 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.
What the Candidate Will Do:
- Define and champion the multi-year technical vision and architecture for foundation models across Search, Recommendations, and Conversational AI.
- Set the architectural standard and drive system design for critical, high-leverage ML platforms across Mobility and Delivery.
- Lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants, resolving complex technical trade-offs across organizational boundaries.
- Define long-term investment areas (build vs fine-tune vs partner models) with clear business rationale and long-term viability.
- Provide principal-level technical leadership, mentoring Staff and Senior Staff engineers, and setting the bar for technical excellence across the entire AI organization.
Basic Qualifications:
- Masters degree or Ph.D in Computer Science, Engineering, Mathematics
- 12+ years of ML experience, including significant work on large-scale deep learning systems.
- Demonstrated ownership of high-impact ML systems in search, recommendations, or conversational AI.
- Deep expertise in transformers, retrieval systems, ranking, and embedding architectures.
- Strong experience with PyTorch and distributed training.
- Proven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level.
- Strong product intuition and ability to connect model improvements to business outcomes.
Preferred Qualifications:
- Track record of successfully launching multi-year, multi-org ML initiatives that drove step-change business outcomes.
- Successfully championed and driven the adoption of multi-year technical roadmaps across multiple large engineering organizations.
- Elevated engineering standards through mentorship and technical leadership, establishing org-wide best practices.
For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.
You 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. You will also be eligible for various benefits.
About UsReady to Ride?
This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Skills Required
- Master's degree or Ph.D. in Computer Science, Engineering, or Mathematics
- 12+ years of machine learning experience
- Significant experience with large-scale deep learning systems
- Ownership of high-impact machine learning systems in search, recommendations, or conversational AI
- Deep expertise in transformers, retrieval systems, ranking, and embedding architectures
- Strong experience with PyTorch and distributed training
- Ability to set technical strategy for a large organization and influence executive-level product roadmaps
- Strong product intuition and ability to connect model improvements to business outcomes
- Track record launching multi-year, multi-organization machine learning initiatives producing significant business outcomes
- Experience driving adoption of multi-year technical roadmaps across large engineering organizations
- Experience elevating engineering standards through mentorship and technical leadership
Uber Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Uber and has not been reviewed or approved by Uber.
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Parental & Family Support — Policies provide a minimum of fully paid parental leave for all parents and financial support for fertility, adoption, and surrogacy, with added credits to ease the transition. Programs extend to family medical leave and parenting support resources, indicating depth beyond baseline offerings.
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Healthcare Strength — Healthcare coverage is described as comprehensive across many countries, with medical, dental, vision, life, disability, and mental health benefits, plus allowances where direct plans are not available. Wellness programs and reimbursements further reinforce access to care.
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Wellbeing & Lifestyle Benefits — Monthly ride and meal credits, free office meals/snacks, fitness stipends, onsite gyms, and wellbeing reimbursements create meaningful everyday value. Home‑office stipends, travel medical coverage, and counseling support round out lifestyle-oriented perks.
Uber Insights
What We Do
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything. Movement is what we do. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real-time. At the incredible speed of now.
Why Work With Us
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.
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