Staff GPU Systems Engineer

Careernet

8 - 12 years

75 - 80 Lacs

bengaluru

Posted:3 weeks ago| Platform:

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Skills Required

c++ triton tvm gpu runtime optimization multi-gpu systems rocm transformer inference. xla mlir

Work Mode

Work from Office

Job Type

Full Time

Job Description

Key Skills:

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:

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