Workload Enablement Engineer

New

Skills

C++/CUDA/HIP Distributed Systems High-Performance Computing (HPC) Large-Scale Distributed Training ML Systems NCCL Performance Engineering Python PyTorch RCCL

We are seeking a skilled Software Engineer specializing in Workload Enablement to join our team. The ideal candidate will be responsible for porting workloads to new platforms while ensuring correctness and stability. You will also build benchmarks and stress tests for various hardware components and conduct deep-dive performance analyses on distributed training and inference systems.

Key Responsibilities
  • Port workloads on new platforms and ensure correctness and stability.
  • Build benchmarks and stress tests for CPU, GPU, memory, storage, and network.
  • Conduct deep-dive performance analyses on distributed training and inference.
  • Perform NCCL/RCCL performance tuning and optimize compute/communication overlaps.
  • Create repeatable CI/lab test harnesses with actionable outputs.
  • Collaborate with systems and fleet engineers to ensure stability and scalability.
Required Skills & Qualifications
  • BS in Computer Science, Electrical Engineering, or equivalent practical experience.
  • 5+ years of experience in ML systems, performance engineering, distributed systems, or HPC.
  • Proficiency in PyTorch and modern LLM training/inference stacks.
  • Familiarity with large-scale distributed training concepts including data/model/pipeline parallelism.
  • Experience with RDMA and debugging/optimizing communication libraries such as NCCL or RCCL.
  • Strong programming skills in Python, C++, and CUDA/HIP.
  • Experience with profiling tools like Nsight, rocprof, and perf.

No forms. Your profile is generated instantly.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: Months

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