Staff Software Engineer Michelangelo Control Plane

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)