Contract GPU kernel optimization role: analyze profiler metrics, identify bottlenecks, and improve kernel performance across modern GPU hardware. Implement and modify C++17, Python, and GPU code using CUDA/HIP/shaders, document optimization decisions, and collaborate as a freelance specialist (20+ hrs/week preferred).
This role is for one of our clients
Compensation: $80-$100 per hour
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.
RequirementsKey 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
- 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
- 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.
Similar Jobs
Information Technology
Campus intern serves as a liaison between CDW sales, university departments, and technology partners; builds relationships, researches campus technology needs, educates stakeholders on CDW solutions, and works 15–25 hours/week while receiving training and mentorship.
Top Skills:
AILivemeeting
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Manage a profitable Farm and Ranch underwriting portfolio using analytics and AI-enabled insights. Write new accounts, pursue renewals, price risk, set terms, and collaborate with agents, brokers, and distribution partners. Mentor junior underwriters, document decisions per company and state standards, and use data to improve submission quality, profitability, and diversification.
Top Skills:
AIAnalyticsDigital Tools
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Lead product convergence and new specialty product development: research, design experiments, define requirements, build roadmaps, manage legacy consolidation, and drive stakeholder alignment to operationalize go-forward products.
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
