Principal Engineer - ML​/AI – Foundation Models

Position: Principal Engineer - ML / AI – Foundation Models
Job-:
Engineer

Location:

San Francisco, CA, United States;
Sunnyvale, CA, United States;
Seattle, WA, United States

Schedule:

Full time, Level 7

Posted:
About the role and team At Uber, machine learning powers some of the most complex real-time decisions in the world — from matching riders with drivers and optimizing marketplace efficiency to personalizing experiences across Mobility and Delivery.

We are making a significant investment in the next generation of machine learning, with a particular focus on building large-scale Foundation Models trained on Uber's proprietary marketplace data.

Unlike general-purpose large language models trained primarily on text and code, our foundation models will learn from rich, heterogeneous sequences of real-world interactions across Uber's ecosystem. These models have the potential to fundamentally transform how we understand and predict marketplace behavior, improve existing ML systems, and unlock entirely new capabilities.

We are looking for an exceptional Principal Engineer, Machine Learning / AI to help lead this effort.

This is a highly strategic, hands-on technical leadership role with the opportunity to shape Uber's foundation model architecture, influence ML investments, and work across multiple engineering and product organizations.  You will help establish deep technical expertise in large-scale model development and accelerate foundation model initiatives across Uber.

Uber’s engineering team executes on the vision and builds the products for the future of urban mobility: deeply understanding our customers to solve their transportation needs with innovative technology. Engineering leaders at Uber move lightning fast to build, test, learn, and iterate, working in small teams that control their own destiny and own their own critical metrics. Leadership helps the vision become a reality and clears obstacles out of the way.

Some of the brightest data scientists, designers, engineers, and marketers in the industry are here to build amazing products on top of leading-edge platforms for data, machine learning, and experimentation.

The products we build are used by millions of riders, drivers, eaters, restaurants, and others to earn money for their families, and get around faster, easier, cheaper, and with less environmental impact.

What you’ll do Architect and build large-scale Foundation Models:
Lead the technical design, development, and training of large sequence-based Transformer models using Uber's proprietary marketplace data.

Define the technical direction:
Help shape Uber's long-term foundation model strategy, including model architectures, training approaches, representation learning, and scaling. Advance representation learning:
Develop powerful embeddings and learned representations that can improve downstream ML models across recommendations, ranking, personalization, marketplace optimization, and other applications. Drive company-wide ML impact:
Partner with engineering and ML teams across Mobility, Delivery, Earner, Merchant, and Consumer experiences to accelerate the adoption and impact of foundation models. Build scalable ML capabilities:
Influence the development of training infrastructure, distributed computing capabilities, and efficient approaches for training and deploying large models. Provide deep technical leadership:
Solve complex modeling challenges, guide architectural decisions, and establish technical best practices for large-scale model development. Collaborate across organizations:
Work closely with senior technical leaders, researchers, and engineering teams to align initiatives, share expertise, and drive innovation. Remain hands-on:
Contribute directly to critical technical decisions, model development, experimentation, and complex engineering challenges while providing Principal-level leadership.

Basic Qualifications BS degree in Computer Science or related technical field, or equivalent experience.  A minimum of 10 years of relevant software engineering experience, with a proven record of technical leadership and innovation. Extensive experience designing, building, and scaling deep learning systems and large-scale AI infrastructure.

Preferred Qualifications Masters/PhD in Computer Science or related technical field. Direct hands-on experience building, training, or scaling large Foundation Models, particularly sequence-based Transformers. Deep expertise in large-scale AI/ML infrastructure, model training systems, and distributed computing. Strong…