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Salary
$232k – $258k per year
Location
In office (San Francisco, Sunnyvale)
Seniority
Staff · 8+ years exp
Visa
H-1B filings in 12 months: 837 · for this role: 451 · green card filings: 258

Confirmed on the employer's own hiring board on Nov 8, 2026. First seen by Alion on Nov 6, 2026. Uber scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Uber is an American mobility and delivery company founded in San Francisco in 2009 that connects independent drivers and couriers with riders and customers through its apps. It operates ride hailing in thousands of cities, a food and grocery delivery business built on the same courier network, a freight brokerage matching shippers with carriers, and an advertising business that sells placement inside those apps. Listed on the New York Stock Exchange since 2019, the company reached sustained profitability in the mid 2020s and now partners with autonomous vehicle developers rather than building self-driving technology itself.

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.

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