SDE IV - GPU Engineer

Glance

5 - 10 years

13 - 14 Lacs

bengaluru

Posted:Just now| Platform:

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Skills Required

telecom accessories c++ automation usage pcie scheduling hardware high performance computing open source

Work Mode

Work from Office

Job Type

Full Time

Job Description

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
model, pipeline, and tensor parallelization.
Establish company-wide
GPU optimization standards, tooling, and SLIs
.
Collaborate with research to design scalable implementations of novel architectures.
Mentor engineers in profiling, tuning, and low-level optimization.
Partner with hardware vendors and infra teams to maximize cluster utilization.

Required Qualifications

5+ 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.
Ability to
design abstractions
balancing flexibility and performance.
Strong knowledge of
NCCL
, NVLink, PCIe, and interconnects.
Familiar with
profiling automation
and performance dashboards.
Excellent technical leadership and mentoring capabilities.

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