We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack.

Key responsibilities include:

• Analyzing and optimizing performance across application, middleware, runtime, and infrastructure layers,networking, storage, Python runtime, GPU utilization, and beyond.
• Developing tooling and metrics that provide deep observability into system performance.
• Collaborating closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements.
• Influencing architecture and design decisions to prioritize latency, throughput, and efficiency at scale.
• Leading investigations into high-impact performance regressions or scalability issues in production.
• Driving performance testing strategies and helping define SLAs/SLOs around latency and throughput for critical systems.

If you have 7+ years of experience in software engineering with a strong track record in performance or reliability of high-scale distributed systems, you might thrive in this role. You should be deeply comfortable with performance profiling tools and tracing systems, have experience optimizing performance across one or more layers of the stack, and have a strong understanding of OS internals, scheduling, memory management, and IO patterns.

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