Senior ML Infrastructure Engineer, Scalable Training

Uber; Seattle (WA); On-site; USD 202,000 - 224,000; Full time

Benefits offered by this job

Bonus program

Equity awards

401(k)

Benefits

Job summary

Uber Seattle is seeking a Senior Software Engineer focused on ML infrastructure within the Mobility Simulation and Planning group. You will build distributed systems, frameworks, and tooling to move models from experimentation to production, enabling scalable simulations and backtests to inform pricing and incentives.

You will collaborate across ML, data science, and platform teams, own critical production components, and mentor engineers through reviews while shaping efficient, reliable

Qualifications

• 6+ years of professional software engineering experience with ML infra.
• Strong Python programming and well-tested code.
• Experience designing and operating distributed systems.
• Experience supporting production ML workflows.
• Understanding performance fundamentals (parallelism, memory).
• Experience delivering projects from design to production.
• Ability to communicate tradeoffs across teams.
• Bachelor’s or Master’s degree in CS or related field.

Responsibilities

• Build shared ML frameworks for development, training, inference, and backtesting.
• Scale distributed workloads across CPU and GPU infrastructure.
• Accelerate experimentation with hyperparameter tuning and tracking.
• Simplify productionization with reliable orchestration and deployment patterns.
• Improve performance by profiling workloads and reducing bottlenecks.
• Collaborate with ML and compute platform teams to extend capabilities.
• Lead projects end-to-end, participate in on-call and reviews.

Skills

Python

Distributed computing

ML infrastructure

Production systems

Communication

Education

Bachelor’s or Master’s degree in CS or equivalent

Tools

Ray

PyTorch

PyTorch Lightning

LightGBM

Job description

Uber Seattle is seeking a Senior Software Engineer focused on ML infrastructure within the Mobility Simulation and Planning group. You will build distributed systems, frameworks, and tooling to move models from experimentation to production, enabling scalable simulations and backtests to inform pricing and incentives.

You will collaborate across ML, data science, and platform teams, own critical production components, and mentor engineers through reviews while shaping efficient, reliable