Staff ML Platform Engineer – Control Plane & Scale

Uber Technologies Inc.; San Francisco (CA); On-site; USD 232,000 - 258,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k)

Job summary

Uber Technologies Inc. is seeking a Staff Software Engineer to anchor the Michelangelo Control Plane, the orchestration backbone for ML pipelines, training jobs, models, and deployments across Uber.

You will own architecture, drive reliability, and lead high‑scale systems initiatives across global data centers and multiple clouds. You will mentor teams, design scalable storage and reconciliation layers, and build APIs and tooling to accelerate hundreds of internal ML and engineering teams.

Qualifications

• 8+ years of professional experience building scalable, fault‑tolerant systems or platforms.
• Proficiency in one or more programming languages (Go, C/C++, Java, Python, or JavaScript).
• Deep expertise in Kubernetes internals: API server, CRDs/controllers, admission webhooks.
• Strong experience with etcd and MySQL.
• Proven track record leading large‑scale engineering projects end‑to‑end.
• Ability to make complex tradeoffs and architect scalable solutions.

Responsibilities

• Own architecture and technical roadmap of the Michelangelo control plane and its API layer.
• Scale storage, reconciliation, and latency characteristics as resources grow.
• Ensure reliability, availability, DR, multi‑region operation, and defined SLOs.
• Mentor engineers; ensure robust, secure and extensible designs.
• Build tooling, APIs, and frameworks to accelerate internal teams.
• Diagnose performance regressions and bottlenecks using observability data.
• Review designs and foster a culture of continuous learning.

Skills

Software architecture

Programming languages

Kubernetes internals

etcd & MySQL

Leadership

Troubleshooting

Education

Bachelor's degree in CS/Engineering

Master's or PhD (preferred)

Tools

CRDs & controllers

etcd

MySQL

Job description

Uber Technologies Inc. is seeking a Staff Software Engineer to anchor the Michelangelo Control Plane, the orchestration backbone for ML pipelines, training jobs, models, and deployments across Uber.

You will own architecture, drive reliability, and lead high‑scale systems initiatives across global data centers and multiple clouds. You will mentor teams, design scalable storage and reconciliation layers, and build APIs and tooling to accelerate hundreds of internal ML and engineering teams.