Sr Staff ML Engineer - Applied AI

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.