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Uber

Staff Software Engineer Michelangelo Control Plane

Sunnyvale, CA, United States
San Francisco, CA, United States

$232,000 to $258,000 USD / year

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Job details

Pay: $232,000 to $258,000 USD / year
Experience: 8+ years of professional experience building scalable, fault-tolerant products or platforms, with a track record of solving strategically important problems.
Posting language: English
Posted: Nov 6, 2026

Original job description

About the role and team

Leading at Uber means setting direction in motion, not waiting for perfect conditions. As a Staff Software Engineer, you will be a technical anchor for the Michelangelo Control Plane, the foundation that orchestrates the lifecycle of ML pipelines, training jobs, models, and deployments for hundreds of teams across Uber. Our mission is to make transportation as reliable as running water, and we need technical powerhouses to build the dependable, high-performance foundation that supports that vision.

This is a role for a proven, large-scale systems thinker who thrives in high-stakes environments. You will navigate the "messy" reality of complex infrastructure spanning global data centers and multiple cloud providers, supporting a wide variety of ML workloads. You will make smart decisions with imperfect information and own the outcomes of architectural choices that affect every ML workflow at Uber. If you lead with clarity, build with heart, and are motivated by the challenge of reliability and efficiency at unparalleled scale, this is where you'll make your mark.

What you'll do

Own the architecture and technical roadmap of the Michelangelo control plane, including its API layer, Kubernetes-native resource model (CRDs and controllers), and state management on etcd and MySQL.
Design and scale the control plane's storage and reconciliation layers, solving consistency, throughput, and latency challenges as the number of managed resources and clusters grows.
Drive reliability, availability, and disaster recovery for the control plane, including multi-cluster and multi-region operation, safe upgrades, and well-defined SLOs.
Provide deep technical mentorship across the stack, ensuring architecture and implementations are robust, extensible, and secure.
Build tooling, APIs, and frameworks that increase the velocity and quality of hundreds of internal engineering and ML teams.
Use observability and data-driven analysis to diagnose performance regressions, controller bottlenecks, and etcd or MySQL contention, and to optimize resource utilization.
Review code and designs while fostering a culture of continuous learning and humility.
Work cross-functionally with ML, Product, Infrastructure, and Operations teams across the globe to drive large-scale projects and align technical investments with business value.

Basic Qualifications

8+ years of professional experience building scalable, fault-tolerant products or platforms, with a track record of solving strategically important problems.
Proficiency in one or more programming languages (e.g., Go, C/C++, Java, Python, or JavaScript) and the ability to define organization-wide standards.
Deep expertise in Kubernetes internals, including the API server, custom resource definitions, controllers and operators, and admission webhooks.
Strong experience with etcd and MySQL.
Proven experience leading large-scale engineering projects through the entire lifecycle from inception to global productionization.
Expertise in making complex engineering and business tradeoffs.
Experience identifying architectural gaps and acting as a multiplier to reduce technical debt across the organization.
Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.

Preferred Qualifications

Experience building or operating ML platforms or workflow orchestration systems.
Experience operating Kubernetes across multiple clusters or regions.
Advanced degree (Master's or PhD) with a focus on distributed computing, system performance, or machine learning.
Experience contributing to open-source projects or leading industry-level technical discussions.
Ability to anticipate future business needs and develop extensible, modular designs that meet long-term scalability targets. (edited)

[8:43 AM]

For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

Ready to Ride?

This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

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More about this job

Skills

ML
Scheduling
Kubernetes
Programming languages
Go
C
C++
Oracle Java
Python
JavaScript
Computer science
Workflow
Distributed computing
Machine learning
Collaboration

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