below marketmost similar roles pay hereabove market
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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. You will define long-term strategies for model architectures, training approaches, and representation learning to create powerful embeddings for recommendations, ranking, and personalization. Key responsibilities include building scalable ML capabilities, influencing training infrastructure, and managing distributed computing for large-scale model deployment. The role requires deep expertise in deep learning systems, pretraining, and sequence modeling. You will solve complex modeling challenges to transform how the company understands real-world interactions across the mobility and delivery ecosystem through innovative, large-scale AI infrastructure.
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.
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.
Contribute directly to model development, experimentation, and complex engineering challenges.
Partner with cross-functional teams to accelerate the adoption of foundation models across the company.
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).
Foundation Models
Transformer Models
Deep Learning
Distributed Computing
Representation Learning
Embeddings
Machine Learning
System Design
AI Infrastructure
Sequence Modeling
Pretraining
Generative AI
NLP
Computer Vision
Deep Learning
LLM
PyTorch
TensorFlow
Keras
JAX
Hugging Face
CUDA
Python
MLOps
LLMOps
RAG
GraphRAG
Vector Databases
LoRA
QLoRA
AWS
GCP
Azure
Distributed Training
Model Serving
Feature Stores
A/B Testing
Machine Learning
Robotics
Python
C++
Trajectory Generation
Reinforcement Learning
Imitation Learning
Generative Models
Distributed ML Pipelines
Motion Planning
Embodied AI
Simulation
Production ML Systems