Principal Engineer - ML / AI – Foundation Models
uberSeattle (WA)
Principal Engineer - ML / AI – Foundation Models
Posted today
uberSeattle (WA)
SENIORITY
Manager
About the role
Overview:
In this Principal Engineer role, you lead the design and training of large-scale foundation models using Uber’s marketplace data to transform how we predict marketplace behavior. You will shape long-term model strategy and architecture while partnering with cross-functional teams across Mobility, Delivery, and Merchants to accelerate impact. You’ll build scalable ML capabilities and push state-of-the-art representations for downstream applications. This is a hands-on leadership position with a focus on real-world impact and technical excellence. Compensation / Benefits bonus program equity 401(k) various benefits in-office collaboration opportunities for impact
Responsibilities:
Architect and build large-scale foundation models (sequence-based Transformer models) Define technical direction for foundation model strategy, architectures, training, and scaling Advance representation learning and embeddings for downstream ML improvements Drive cross-functional ML impact across Mobility, Delivery, Earner, Merchant, and Consumer experiences Build scalable training infrastructure and distributed computing capabilities Provide deep technical leadership and establish best practices for large-scale model development Collaborate with senior leaders, researchers, and engineers to align initiatives Remain hands-on in critical technical decisions and model development
Key requirements:
BS degree in Computer Science or related field; equivalent experience ≥10 years software engineering with proven technical leadership Extensive experience designing, building, and scaling deep learning systems and AI infrastructure Masters/PhD preferred (as per description) Direct hands-on experience with large Foundation Models, especially sequence-based Transformers Deep expertise in large-scale AI/ML infrastructure and distributed computing Strong understanding of modern deep learning techniques (pretraining, embeddings, sequence modeling) Strong software engineering and system design skills Proven ability to lead complex technical initiatives cross-functionally cross-functional collaboration technical leadership problem solving Foundation Models sequence-based Transformers distributed training
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