**About the Role** We are seeking a Staff Cloud Engineer to join Uber’s Fleet Engineering organization. This role provides technical leadership and architectural ownership for the design, build, and operation of Uber’s next-generation cloud platform qualification and performance engineering. You will define the long-term direction of how Uber evaluates, selects, and continuously validates infrastructure at scale, while delivering measurable improvements across performance, efficiency, and reliability. You’ll drive end-to-end performance strategy and execution, building scalable software systems, automation, and tooling that accelerate infrastructure decisions across Uber. You will partner closely with infrastructure, SRE, internal service and product teams, and cloud and xPU vendors to influence platform roadmaps and system architecture. You’ll work across multi-cloud, containerized, virtualized, and bare-metal systems, executing qualifications and deep performance analyses across the stack—from hardware and Linux kernel runtimes to distributed application services. Beyond running benchmarks, you’ll lead complex investigations into performance anomalies, evolve existing benchmarks, and architect new workloads that better reflect Uber’s production patterns. This role offers broad collaboration across Uber and with external partners, including hyperscalers, silicon vendors, and open-source communities, to shape the next generation of Uber’s infrastructure. It is well suited for engineers with strong systems and software engineering depth, a hardware–software co-design mindset, and a passion for building durable, high-leverage engineering platforms. \-\-\-\- What the Candidate Will Do ---- 01. Design, develop, and maintain production-grade software systems that automate performance testing, regression detection, and decision-making at scale. 03. Develop and evolve representative workloads and benchmarks (compute, storage, network, ML/AI), integrating stress, chaos, and regression testing to validate hardware and platform choices. 05. Lead end-to-end performance analysis and optimization across hardware, firmware, Linux kernel, runtimes, orchestration layers, and distributed services using advanced profiling and observability tools (perf, eBPF, flamegraphs, tracing frameworks). 07. Build and scale automation and observability tooling (Go/Python/Java, Kubernetes/Docker) integrated with CI/CD pipelines for performance gating, telemetry, alerting, and anomaly detection. 09. Partner with hyperscalers and silicon vendors (CPU, GPU, and accelerator providers) to evaluate emerging instances, kernels, and infrastructure technologies, translating findings into clear roadmap recommendations and investment decisions. 11. Influence infrastructure and platform architecture decisions by identifying systemic bottlenecks, inefficiencies, and opportunities for high-leverage improvements. 13. Drive execution quality by writing and reviewing design documents, setting technical direction and milestones, mentoring engineers, and clearly communicating insights and results to senior stakeholders and leadership. \-\-\-\- Basic Qualifications ---- 1. 8+ years of experience in software engineering, systems engineering, or performance engineering, with demonstrated ownership of complex, multi-quarter initiatives. 2. Bachelor’s degree or higher in Computer Science, Computer Engineering, or a related field (or equivalent practical experience). 3. Proficiency in two or more of Go, Python, Java, C/C++, with strong computer science fundamentals and disciplined testing and automation practices. 4. Deep hands-on experience with Linux internals (CPU scheduling, memory management, I/O, networking) and performance tooling (perf, eBPF, flamegraphs, tracing frameworks). 5. Experience building and operating distributed systems, containerized platforms, and microservices using Docker and Kubernetes. 6. Proven ability to communicate clearly through design documents, postmortems, and technical reviews, and to lead cross-functional technical efforts. \-\-\-\- Preferred Qualifications ---- 1. Experience tuning or operating databases, stream processing, batch, or ML platforms (e.g., Presto, Spark, Kafka, PyTorch, JAX). 2. Familiarity with distributed tracing and observability systems (OpenTelemetry, Jaeger). 3. Performance engineering experience across databases, streaming, batch, or ML workloads, including exposure to GPU/xPU or Arm-based systems. 4. Experience building CI/CD performance gates, regression detectors, and large-scale observability pipelines. 5. Large-scale fleet experience, including OS imaging and provisioning, configuration rollout, hardware health monitoring, and data center networking fundamentals. 6. Full-stack bonus: backend systems (e.g., MySQL) and light UI or visualization work (e.g., React, Tableau) for performance reporting and dashboards. For Seattle, WA-based roles: The base salary range for this role is USD$211,000 per year - USD$234,000 per year. 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. More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits). Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A). 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.