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$196,000–$264,812.
Based on 240 similar postings.
Employer
About Uber
Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.
The Principal Engineer - ML / AI – Foundation Models joins the engineering team to lead the development of large-scale foundation models trained on proprietary marketplace data. This hands-on technical leadership role involves architecting and building large sequence-based Transformer models to improve marketplace behavior predictions and unlock new capabilities. You will define long-term strategies for model architectures, training approaches, and representation learning while developing powerful embeddings for downstream applications like ranking and personalization. Key responsibilities include building scalable ML capabilities, influencing training infrastructure, and solving complex modeling challenges across Mobility and Delivery. The role requires deep expertise in deep learning systems, distributed computing, and sequence modeling to solve real-world marketplace problems. You will collaborate across organizations to accelerate the adoption of these models across the entire ecosystem.
What does a Engineer earn in California?
Median $199500 from 103 postings across 31 companies.
Architect and build large-scale sequence-based Transformer models using proprietary marketplace data.
Define the long-term technical strategy for model architectures, training approaches, and scaling.
Develop powerful embeddings and learned representations to improve downstream ML models for ranking and personalization.
Influence the development of training infrastructure and distributed computing capabilities for large models.
Solve complex modeling challenges and establish technical best practices for large-scale model development.
Drive the adoption and impact of foundation models across Mobility, Delivery, and Merchant experiences.
Contribute directly to model development, experimentation, and critical engineering challenges.
What we're looking for
BS degree in Computer Science or related technical field, or equivalent experience.
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.
Masters/PhD in Computer Science or related technical field (preferred).
Direct hands-on experience building, training, or scaling large Foundation Models, particularly sequence-based Transformers (preferred).
Deep expertise in large-scale AI/ML infrastructure, model training systems, and distributed computing (preferred).
Strong understanding of modern deep learning techniques, including pretraining, representation learning, embeddings, and sequence modeling (preferred).
Strong software engineering and system design skills (preferred).
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