Senior ML Infrastructure Engineer — Systems Architect for Scale

Uber; Seattle (WA); On-site; USD 232,000 - 258,000; Full time

Benefits offered by this job

401(k) plan

Bonus program

Equity award

Benefits

Job summary

Uber seeks a Staff Software Engineer - ML Infra to architect mission-critical ML and backend systems powering trust across its global marketplace. You will design scalable ML infrastructure to support payments, pricing simulations, and large-scale models.

The role emphasizes end-to-end ownership, deep systems thinking, and collaboration with Product, Science, and Ops, mentoring engineers and delivering reliable, low-latency services in a fast-paced environment.

Qualifications

• 9+ years of experience building ML backend systems.
• Bachelor's degree required in CS/CE or related field.
• Familiar with AI/ML frameworks (PyTorch, TensorFlow).
• Experience with foundational models or LLMs at scale.
• Solid understanding of ML algorithms and data pipelines.
• Proven MLOps and ML Infrastructure experience including Kubernetes.

Responsibilities

• Design and build long-lasting ML infra artifacts to reduce complexity and increase velocity.
• Solve high-impact problems at the intersection of low latency and high correctness.
• Lead adoption of key frameworks and drive design reviews.
• Collaborate with Product, Science, and Ops to translate requirements into roadmaps.
• Mentor engineers and raise engineering standards across the org.

Skills

ML Infra

System Design

Distributed Systems

MLOps

Kubernetes

Python

PyTorch

TensorFlow

Education

Bachelor's degree in Computer Science or related

Tools

Kubernetes

PyTorch

TensorFlow

Spark

Job description

Uber seeks a Staff Software Engineer - ML Infra to architect mission-critical ML and backend systems powering trust across its global marketplace. You will design scalable ML infrastructure to support payments, pricing simulations, and large-scale models.

The role emphasizes end-to-end ownership, deep systems thinking, and collaboration with Product, Science, and Ops, mentoring engineers and delivering reliable, low-latency services in a fast-paced environment.