Hirely is recruiting on behalf of a hiring partner for a remote CUDA / GPU Engineering opportunity
supporting a project with a leading AI research organization. Contributors will optimize and evaluate GPU kernels across modern hardware environments, using performance profiling and low-level GPU programming expertise to improve efficiency, utilization, and execution speed.

What You’ll Do:
- Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization.
- Use GPU profiler metrics such as
L2 cache hit rate, L2 throughput, occupancy, and related performance signals
to identify bottlenecks.
- Review existing GPU kernel implementations and determine optimization opportunities.
- Write, modify, and evaluate
C++17, Python, and GPU programming code
.
- Apply CUDA, HIP, shader programming, or related GPU programming models to improve kernel performance.
- Evaluate kernel behavior across modern GPU architectures.
- Document optimization decisions and explain performance tradeoffs clearly.




- Work on challenging performance-engineering problems where strong GPU expertise is required.

Who We’re Looking For:
- 1+ year of skilled or graduate-level GPU programming/research experience.
- Strong proficiency in C++ through C++17
.
- Working knowledge of
Python and Git
.
- Experience with at least one GPU programming model, including: CUDA, HIP, Slang, HLSL, GLSL or similar GPU/kernel programming technologies
- Strong understanding of
GPU performance profiling and optimization
.
- Experience analyzing GPU performance metrics and identifying kernel bottlenecks.
- Ability to optimize GPU kernels without requiring extensive knowledge of the underlying application.
- Availability for
20+ hours per week
.

Preferred Qualifications:
- Experience with CUDA C++ Core Libraries.
- Inline PTX or low-level GPU programming experience.
- Tensor Core optimization experience.
- NVIDIA Blackwell optimization experience.
- Experience with
NVIDIA Nsight Compute
.
- Backgrou

📌 CUDA Engineering Expert | $500/Task (India)
🏢 Hirely
📍 India