Senior ML Infra Engineer: Architect Scalable Systems

Uber; San Francisco (CA); On-site; USD 202,000 - 224,000; Full time

Benefits offered by this job

Bonus program

Equity

401(k)

Benefits

Job summary

Uber is seeking a Senior Software Engineer focused on ML Infra to architect mission-critical ML data and backend systems powering a trusted global marketplace. You will design scalable platforms, from ensuring accurate payments to building simulation engines for pricing decisions, while maintaining performance and reliability at scale.

You will lead cross-functional efforts, mentor engineers, and own end-to-end delivery from design to production debugging.

Qualifications

• 6+ years of experience building ML models to solve business problems.
• Familiar with PyTorch and TensorFlow.
• Experience developing foundational models or LLMs for production use at scale.
• Strong understanding of ML algorithms and deployment considerations.
• Experience with MLOps including orchestration, data pipelines, and large-scale jobs.

Responsibilities

• Design and build long-lasting artifacts that reduce complexity and increase developer velocity.
• Solve high-impact problems at the intersection of low latency and high correctness.
• Lead organization-wide development and adoption of key frameworks and promote best practices.
• Partner with Product, Science, and Ops to translate business requirements into technical roadmaps.
• Mentor engineers and raise the bar for engineering excellence across the org.

Skills

ML model development

PyTorch

TensorFlow

LLMs

ML algorithms

MLOps

Education

Bachelor's degree in Computer Science/Computer Engineering or related fields

Tools

Kubernetes

Job description

Uber is seeking a Senior Software Engineer focused on ML Infra to architect mission-critical ML data and backend systems powering a trusted global marketplace. You will design scalable platforms, from ensuring accurate payments to building simulation engines for pricing decisions, while maintaining performance and reliability at scale.

You will lead cross-functional efforts, mentor engineers, and own end-to-end delivery from design to production debugging.