Lead Runtime Engineer

AMD AMD · Semiconductors · MARKHAM, Canada · Engineering

Lead Runtime Engineer at AMD to support and develop GPU-compute language runtime libraries for the ROCm platform on Windows, focusing on AI and HPC applications. Involves deep technical collaboration with customers and partners to resolve driver-level challenges and ensure successful deployment of AMD GPU technologies.

What you'd actually do

  1. Design, develop, and optimize GPU language runtime components for Windows within the AMD ROCm platform
  2. Implement and enhance runtime functionalities that interface with Windows kernel-mode and user-mode GPU drivers
  3. Conduct deep performance analysis using profiling tools, instrumentation, and hardware counters
  4. Identify, diagnose, and eliminate performance bottlenecks across driver, runtime, and compute pathways
  5. Work with AMD architecture teams to influence future GPU hardware and software features with a focus on performance scalability

Skills

Required

  • C/C++
  • Windows GPU kernel-mode drivers (WDDM, KMDF/WDF)
  • performance profiling tools (WinDbg, GPUView, WPA, ETW tracing, PIX, vendor profilers)
  • deep-dive debugging and optimization using hardware counters, scheduling analysis, and memory utilization metrics
  • developing or optimizing runtime systems such as compute runtimes, language runtimes, device runtimes, or driver-adjacent software
  • concurrency, synchronization primitives, and multi-threaded performance tuning
  • Windows OS internals, memory models, kernel/user transition costs, and driver framework best practices
  • debuggers, profilers, static analyzers, and source-control systems (Git/GitHub)

Nice to have

  • Windows Display Driver Model (WDDM), DXGI, Direct3D, compute driver components, or command submission pipelines
  • AI, graphics, and HPC workloads

What the JD emphasized

  • Windows graphics and compute driver enablement
  • performance analysis
  • performance bottlenecks
  • performance scalability
  • peak performance
  • performance best practices
  • performance profiling tools
  • performance-critical issues
  • highly optimized driver and runtime technologies

Other signals

  • AMD ROCm platform
  • Windows graphics and compute driver enablement
  • AI and high-performance computing applications
  • GPU compute runtime performance