Staff GPU Systems Engineer

3 days ago

Bengaluru, Karnataka, India Careernet Full time ₹ 12,00,000 - ₹ 24,00,000 per year

Key Skills: Triton, C++, GPU Runtime Optimization, Multi-GPU Systems, TVM, XLA, MLIR, ROCm, Transformer Inference.

Roles & Responsibilities:

  • Architect high-performance inference runtimes, kernel dispatchers, and memory planners for large diffusion and transformer workloads.
  • Lead investigations into cross-GPU performance bottlenecks, communication overheads, and scheduling inefficiencies.
  • Drive multi-GPU parallelism strategies, including model, pipeline, and tensor parallelization.
  • Establish company-wide GPU optimization standards, tooling, and SLIs.
  • Collaborate with research teams to design scalable implementations of novel architectures.
  • Mentor engineers in profiling, tuning, and low-level optimization practices.
  • Partner with hardware vendors and infrastructure teams to maximize GPU cluster utilization.

Experience Requirement:

  • 8 - 12 years in high-performance computing, GPU runtime systems, or ML infrastructure.
  • Proven expertise in CUDA, Triton, C++, with deep understanding of GPU scheduling, occupancy, register usage, and tensor cores.
  • Experience building and maintaining distributed inference or training systems.
  • Strong knowledge of NCCL, NVLink, PCIe, and interconnects.
  • Familiarity with profiling automation and performance dashboards.
  • Demonstrated technical leadership and mentoring capabilities.

Education: B.Tech.

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