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Uber is seeking a Cloud Performance Engineer to optimize cloud and bare-metal infrastructure for Uber-scale workloads, analyzing and improving performance end-to-end from hardware to application-level services and distributed systems.

Requirements

• Proficiency in one or more languages (Golang, Java, Python, or C/C++)
• Hands-on experience in performance profiling and tuning with tools like flamegraphs, Linux perf, eBPF, or similar.
• Solid understanding of OS internals, including CPU scheduling, memory management, and networking.
• Familiarity with Kubernetes/Docker and distributed systems.
• Understanding of observability concepts (SLIs/SLOs, alerting, telemetry)
• Experience tuning databases, stream processing, batch or ML platforms (e.g. PyTorch, JAX)
• Familiarity with microservices debugging and distributed tracing (OpenTelemetry, Jaeger)

Responsibilities

• Analyze and optimize system/application performance across cloud, bare metal, and container workloads.
• Collaborate with hyperscalers and silicon providers to evaluate emerging server, silicon, and infrastructure technologies for performance impact.
• Use profiling tools (perf, eBPF, flamegraphs, tracing frameworks) to debug and resolve high-impact performance issues
• Contribute to Uber’s internal benchmarking and profiling frameworks to deliver real-world performance insights.
• Partner with SREs and Infra engineers to automate performance analysis and observability, ensuring scalable alerting, telemetry, and diagnostics across services.
• Drive architectural and tooling decisions that influence how Uber builds, monitors, and scales its systems.

Other

• 3+ years of experience in hardware or systems-level performance engineering, SRE, or backend infrastructure development.
• Ability to work independently troubleshoot and automate solutions.
• Bachelor's, Master's, or Ph.D. degree in Computer Science or related field (not explicitly mentioned but implied)
• For San Francisco, CA-based roles and Sunnyvale, CA-based roles, you will be expected to spend at least half of your work time in your assigned office.
• Unless formally approved to work fully remotely, Uber expects employees to be in-office for a significant portion of their time.