CUDA Engineering Expert

EngineerEngineerPart TimeRemoteMid LevelTeam 501-1,000Since 2002H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

2 days ago

Salary

$80 - $100 / hour

Seniority

Mid Level

Job Description

CUDA Engineering Expert

Weekday

Role Description We are 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. - 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 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 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 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.

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