Workload Porting & Performance Engineer
Evaluates new hardware platforms by porting benchmarks and workloads, analyzes performance across compute/memory/networking, identifies bottlenecks, and optimizes for AI systems. Requires expertise in performance analysis, system architecture, and debugging across hardware/software boundaries.
About the job
Key Responsibilities
- Port and enable benchmarks and real-world workloads on new hardware platforms.
- Evaluate system performance across compute, memory, storage, and networking subsystems.
- Identify and analyze performance bottlenecks and inefficiencies.
- Adapt and optimize workloads to better utilize hardware capabilities.
- Develop and run performance experiments and profiling workflows.
- Compare expected vs. observed performance and provide feedback to hardware architecture teams, performance modeling teams, system and software engineers.
- Debug issues across the stack, including software, runtime, and hardware interactions.
- Provide actionable insights to guide platform readiness and deployment decisions.
Qualifications
- Experience with performance analysis, benchmarking, or workload optimization.
- Strong understanding of system architecture, including CPU/GPU, memory, and I/O subsystems.
- Experience porting or adapting workloads across different hardware platforms.
- Familiarity with profiling tools and performance debugging techniques.
- Ability to identify root causes of performance issues across hardware/software boundaries.
- Experience working in large-scale or distributed system environments.
Preferred Skills
- Experience with AI/ML workloads, including training or inference systems.
- Familiarity with GPU or accelerator-based systems.
- Experience working with low-level performance tools (profilers, tracing, microbenchmarks).
- Background in systems software, compilers, or runtime optimization.
- Experience collaborating with hardware and architecture teams on performance validation.
Skills
Performance Analysis, Benchmarking, Workload Optimization, Cpu, GPU, Profiling Tools, System Architecture, Distributed Systems, Ai/Ml Workloads, Profilers, Tracing, Microbenchmarks
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