Performance Engineer 6

Netflix is a world leader in Performance Engineering, focused on pushing the boundaries of storytelling through technology. They are seeking a highly experienced Performance Engineer to optimize GPU infrastructure efficiency and large-scale AI/ML workloads, ensuring maximum performance while managing costs and resources. Responsibilities: Drive efficiency and performance optimization across our large-scale infrastructure; Collaborate with ML Platform and Data Science teams to build and enhance comprehensive profiling, tracing, and observability capabilities for GPU workloads; Analyze and resolve complex performance bottlenecks across the entire stack, including hardware, drivers, OS, Kubernetes/scheduling, networking, storage, and application code; Evaluate and guide the adoption of new GPU architectures, interconnects, and cloud vendor services to maximize performance and cost efficiency within Netflix's AI/ML ecosystem; Share knowledge by documenting best practices, contributing to Netflix Tech Blogs, and presenting at industry and vendor forums Qualifications: 10+ years of experience in systems performance analysis and optimization with a focus on large-scale distributed systems; Deep understanding of GPU architecture, kernels, and ML frameworks; Experience in building and using CPU and GPU profiling and other performance analysis tools; Expertise in identifying and resolving performance bottlenecks within the AI/ML infrastructure and software stack; Experience with container orchestration platforms such as Kubernetes; Experience with performance analysis and optimization in a multi-tenant, cloud-native environment; Strong programming skills in languages such as Python and Java Required Skills: Systems Performance Analysis, Distributed Systems, GPU Architecture, GPU Kernels, ML Frameworks, CPU Profiling, GPU Profiling, Performance Analysis Tools, AI/ML Infrastructure, Container Orchestration, Kubernetes, Cloud-native Environment, Python, Java