Staff Software Engineer

About The Role The Compute Platform team's mission is to build the next generation of Uber's container orchestration platform on Kubernetes that is secure, reliable, scalable, and highly efficient. At Uber we have a complex infrastructure spanning both on-prem data centers and cloud. It supports a diverse variety of workloads (stateless, stateful, batch, streaming, ML/AI), each different in its characteristics and requirements. We build solutions to enable user applications/jobs to be deployed anywhere in the world with the touch of a button. We build abstractions to enable Uber developers with infrastructure that just works for every application type. We actively work with the open-source community including Kubernetes and contribute back. We are at the cutting edge of technology and the team regularly presents at industry conferences. Here are some KubeCon sessions (2024 session + video , 2023 session1 , session2 ) where we have talked about our team's work. We are looking for a strong technical leader to drive and craft the technical roadmap & delivery of key initiatives in the Compute Platform org.

What The Candidate Will Need / Bonus Points ---- What the Candidate Will Do ----

• Lead initiatives through all stages of the project lifecycle, from ideation and design to project planning and execution, by understanding business requirements and providing effective solutions.
• Develop and document high-quality code to address strategically important problems.
• Productionize systems across Uber's fleet while carefully monitoring and evolving the solutions based on production data.
• Foster collaboration across multiple teams to achieve successful delivery of projects.
• Mentor engineers to cultivate their leadership capabilities.
• Represent the team in both internal and external forums.

Basic Qualifications

• Bachelor's degree in Computer Science or related field.
• Experience programming in multiple languages such as Go, Java, Python, C/C++.
• 8+ years of experience in low-level systems, distributed systems, or similar technologies.
• Strong background in containerization, resource scheduling, and cluster management at scale.
• Hands-on experience with performance tuning, reliability engineering, and cost optimization in compute environments.
• Background in large-scale backend infrastructure.

Preferred Qualifications

• Working experience in cluster management solutions such as Kubernetes or Mesos.
• Understanding of container technologies such as docker or containerd.
• Knowledge of operating systems and Linux kernel. ~~ ~~