Sr Staff ML Engineer - Applied AI at Uber – San Francisco | Jobyssey

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.

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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.

Ready 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.

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