Work Snapshot

Type:

Contract

Location:

Remote

Commitment:

10-40 hrs/week

Compensation:

$300

What You'll Be Doing

- Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization.

- Use profiler metrics such as L2 cache hit rate, L2 throughput, and occupancy to guide kernel improvements.

- Review GPU kernel implementations and identify bottlenecks.

- Write, modify, and reason about C++17, Python, and GPU programming code.

- Apply CUDA, HIP, shader programming, or related kernel programming expertise to improve performance outcomes.

- Document optimization decisions clearly, including when specific profiler metrics are or are not useful.

What We're Looking For

- Fluent in core C++ features through C++17.

- Working knowledge of Python and Git.

- Fluent in at least one GPU programming model, such as CUDA, HIP, Slang, HLSL,



GLSL, or related kernel programming.

- Have robust relevant experience in the domain working with GPUs.

- Strong understanding of GPU profiler performance metrics and how to use them to optimize kernels.

- Ability to optimize GPU kernels without needing deep prior context on every algorithm.

Application Process

- Submit your application through the Easy Apply button.

- Each application will be reviewed against the role requirements.

- Candidates who meet the requirements will receive an email with the next steps.

- Follow the instructions provided in the email to complete the remainder of the application process.

📌 GPU Developer | Remote (Canada)
🏢 CodeGeniusRecruit
📍 Canada