Engineering Manager II

Uber

Hybrid

Quick summary

Work type: Hybrid
Location: Seattle, WA · Sunnyvale, CA
Salary: $232,000–$232,000 / yr
Posted: 5 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $193k

This role $232k

$135k most similar roles pay here $251k

This role pays more than 69% of similar roles. Most pay $145,862–$239,400 — the shaded band above. At the midpoint, this role pays about $232k versus about $193k for comparable roles.

Based on 238 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.

Uber currently has 95 open roles on FindRole.

Listed pay typically runs $232,000–$232,000 across 76 roles with salary data.

Most-posted roles

View all roles at Uber

At a glance

TL;DR · Engineering Manager II

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As an Engineering Manager II at Uber’s AI platform Michelangelo, you will lead the ML Training team responsible for building and operating distributed training systems for multi-GPU/TPU environments. Your role involves driving the technical vision and strategy for large-scale ML platforms, leading a team of engineers to develop scalable infrastructure that supports diverse ML applications across Uber. You will ensure the reliability and cost efficiency of production models while collaborating with product teams to translate business needs into platform capabilities. Key responsibilities include guiding architecture decisions, improving ML velocity through better tooling, and mentoring engineers. The ideal candidate has extensive experience in large-scale distributed systems, ML/DL frameworks like Ray, PyTorch, TensorFlow, and Jax, as well as a strong background in software development with Python, Java, Go, or C++.

Skills

Python Ray PyTorch TensorFlow Kubernetes AWS GCP OCI Docker CI/CD MLOps PostgreSQL Redis Prometheus Java Go C++ Scalability Reliability

What you'll do

Define and drive the technical vision for scalable ML platforms.
Lead a team of engineers to develop high-impact ML infrastructure.
Ensure scalability, reliability, and cost efficiency in production models.
Collaborate with product teams to translate business needs into platform capabilities.
Guide architecture decisions across distributed systems and developer experience.
Improve ML velocity through better tooling and workflows.
Mentor engineers and raise the bar on system design and execution.

What we're looking for

8+ years of experience in building large-scale distributed systems in production.
Proven leadership in managing and growing engineering teams for at least 2 years.
Expertise in machine learning frameworks like PyTorch, TensorFlow, and Jax.
Strong background in software development using Python, Java, Go, or C++.
Experience leading complex technical projects and setting technical direction.
Deep understanding of large distributed training systems on multi-GPU/TPU environments.
Familiarity with cloud provider services for ML training and deployment.

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