**About the Role** We are building out a team dedicated to optimizing the performance of Uber’s critical workloads. Our mission is to ensure that workloads running across Uber’s infrastructure perform at peak efficiency, minimizing latency, maximizing throughput and ensuring optimal resource usage. A key focus of the team is to develop systems for continuous workload performance analysis, regression detection and optimization, enabling performance improvements at scale. The role emphasizes designing and building systems that help optimize workload performance across a diverse infrastructure, including bare metal hosts, VMs, on-prem data centers, and multiple cloud vendors. You will work closely with other teams to identify performance bottlenecks, mitigate inefficiencies, and address challenges such as noisy neighbor problems in colocated environments. Additionally, you will be responsible for building systems that help quickly troubleshoot performance issues in production, ensuring Uber’s workloads remain highly performant and stable. As part of this growing team, you will have the opportunity to shape the future of performance-driven workload optimization at Uber, contributing to the development of systems and tools to drive these improvements. As a member of this new team, you will leverage your software engineering and systems expertise to build systems that help optimize the performance of Uber’s critical workloads. You will play a key role in driving performance improvements, building systems for troubleshooting production performance issues, and contributing to the development of systems for continuous workload performance analysis and optimization. 1. Design and build systems to help conduct in-depth performance analysis and identify bottlenecks, regressions, inefficiencies, and opportunities for optimization in workload performance 2. Build systems to help quickly troubleshoot and resolve performance issues in production environments to maintain stability and high performance. 3. Collaborate with other teams to ensure Uber’s workloads perform optimally, addressing challenges such as noisy neighbor problems in shared environments 4. Write clean, efficient code (Go) with workload performance and automation as primary goals 5. Perform low-level debugging for production performance issues and optimize resource allocation, including CPU, memory, and I/O 6. Participate in code reviews, focusing on best practices for building performance systems 7. Help shape the team’s long-term strategy for building workload performance optimization systems \-\-\-\- Basic Qualifications ---- 1. 8+ years of experience 2. BS, MS, or PhD in computer science, or similar technical fields with hands-on performance engineering experience 3. Strong experience or interest in performance analysis, tuning, benchmarking and troubleshooting performance issues in production on Linux systems 4. Proficiency in multiple programming languages (e.g., C/C++, Go) 5. Proven ability to collaborate across teams to build systems at scale 6. Excellent communication and analytical skills with a focus on performance analysis and reporting, postmortems, and technical documentation \-\-\-\- Preferred Qualifications ---- 1. Strong understanding of Linux kernel internals with a focus on workload performance 2. Expertise in hardware and software performance tuning at scale 3. Expertise in profiling tools (e.g., perf, eBPF) and debugging complex performance issues 4. Experience with containerization and orchestration platforms (Kubernetes, Docker) 5. Familiarity with cloud infrastructure (AWS, GCP), particularly in tuning for large-scale workload performance 6. Comfortable working with high-performance on-prem and cloud-based infrastructure 7. Experience contributing to the development of systems for performance analysis and optimization We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together. Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. \*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to [accommodations@uber.com](mailto:accommodations@uber.com).