CUDA Engineering Expert

$80-$100 / hr

Hourly contract

Remote

BRK

210 hired this month

Early applicant

$80-$100

per hour

Posted by Mercor

mercor.com

Application

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Resume |Domain Expert Interview |CUDA Expert Assessment |Work Authorization

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All application steps are reused whenever another role requires the same step, so you never have to upload your resume or take the same interview twice

1. Role Overview

Mercor is seeking GPU kernel optimization experts to contribute to a project with a leading AI lab. This opportunity is designed for freelancers with strong C++ skills, practical GPU programming experience, and the ability to improve kernel performance using profiler-guided analysis. You’ll help evaluate, optimize, and reason about GPU kernels across modern hardware environments. This is a contract-based opportunity for specialists who enjoy squeezing performance out of modern GPU architectures.

2. Key Responsibilities

Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization
Use profiler metrics such as L2 cache hit rate, L2 throughput, occupancy, and related signals to guide kernel improvements
Review GPU kernel implementations and identify bottlenecks without requiring extensive background in the underlying algorithms
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

3. Ideal Qualifications

Available to work at least 20 hrs/wk
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
At least 1 year of professional or graduate-level research experience 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
Experience with CUDA, HIP, CUDA C++ Core Libraries, inline PTX assembly, or tensor core-level optimization is a plus
Experience optimizing kernels for NVIDIA Blackwell hardware is a plus
Familiarity with NSight Compute is a plus
Prior experience with GPU hardware organizations such as NVIDIA, AMD, or Qualcomm is a plus
Open-source contributions related to GPU kernel optimization are a plus

4. Application Process

Submit your resume or relevant technical background to get started
Qualified applicants may be asked to complete a brief technical assessment or submit additional information

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Contract and Payment Terms

You will be engaged as an independent contractor.
This is a fully remote role that can be completed on your own schedule.
Projects can be extended, shortened, or concluded early depending on needs and performance.
Your work at Mercor will not involve access to confidential or proprietary information from any employer, client, or institution.
Payments are weekly on Stripe or Wise based on services rendered.
Please note: We are unable to support H1-B or STEM OPT candidates at this time.

About Mercor

Mercor partners with leading AI labs and enterprises to train frontier models using human expertise. You will work on projects that focus on training and enhancing AI systems. You will be paid competitively, collaborate with leading researchers, and help shape the next generation of AI systems in your area of expertise.

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