We are sharing a specialised consulting opportunity for experienced CUDA Engineering Experts with strong expertise in CUDA, C++, GPU kernel optimisation, GLSL, WebGPU, profiling, and high-performance computing to contribute to an advanced GPU-engineering and AI training project.
Selected professionals will analyse and optimise GPU kernels, improve CUDA and C++ codebases, work with shader and WebGPU workflows, and document performance improvements across modern GPU architectures. The work requires strong low-level performance engineering, rigorous profiling, and the ability to translate technical findings into clear, actionable recommendations. No prior experience in AI is required.
Key Responsibilities
CUDA Kernel Analysis & Optimisation
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Analyse and optimise GPU kernels using CUDA
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Identify performance bottlenecks affecting computational throughput
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Improve kernel efficiency across modern GPU hardware
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Apply targeted optimisation techniques based on profiling results
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Validate performance gains using quantitative benchmarks
GPU Profiling & Performance Engineering
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Profile GPU workloads using tools such as Nsight, Visual Profiler, or comparable platforms
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Diagnose memory, compute, occupancy, and execution bottlenecks
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Evaluate kernel performance across different hardware generations
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Develop data-driven optimisation strategies
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Document measurable changes in latency, throughput, and resource utilisation
C++ & CUDA Codebase Refactoring
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Refactor CUDA and C++ code for improved maintainability and efficiency
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Improve architecture and organisation within performance-critical codebases
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Reduce unnecessary complexity while preserving functionality
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Adapt implementations for portability across GPU architectures
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Apply high-performance computing best practices throughout development
GLSL & WebGPU Development
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Implement shader logic using GLSL
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Develop graphics and compute workflows using WebGPU
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Integrate shader-based processing into existing systems
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Evaluate performance trade-offs across GPU execution environments
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Maintain compatibility and consistency across pipeline components
Technical Evaluation & Design
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Contribute expertise to GPU architecture and performance-design discussions
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Evaluate new GPU-based implementation approaches
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Assess technical trade-offs across performance, maintainability, and scalability
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Support definition of meaningful performance metrics
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Recommend practical approaches based on profiling and benchmarking evidence
Technical Documentation & Collaboration
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Document optimisation strategies, benchmark results, and technical findings
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Produce clear reports describing performance improvements
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Communicate complex GPU behaviour to technical stakeholders
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Collaborate with remote and cross-disciplinary project teams
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Share relevant developments in GPU programming and performance engineering
Ideal Profile
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Demonstrated expertise in CUDA programming
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Strong track record of GPU kernel performance optimisation
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Advanced C++ development experience
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Experience working in high-performance computing environments
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Hands-on experience with GLSL and WebGPU
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Strong understanding of graphics or compute shader development
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Proficiency with GPU profiling tools such as Nsight, Visual Profiler, or equivalent
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Ability to reason about memory behaviour, kernel execution, and hardware utilisation
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Strong analytical skills for evaluating performance across GPU architectures
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Experience refactoring performance-critical codebases
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Excellent written and verbal technical communication skills
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Comfortable collaborating in remote, cross-disciplinary environments
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No prior AI-training experience is required
Engagement Details
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Independent contractor engagement
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Fully remote
- Compensation: $60–$100/hour
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Work will involve CUDA kernel optimisation, GPU profiling, C++ development, GLSL, WebGPU, and performance analysis
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Strong low-level GPU performance expertise is central to this engagement
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Assignments may involve kernel benchmarking, bottleneck analysis, codebase refactoring, shader development, and architectural evaluation
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Project scope, workload, hardware targets, and performance requirements may evolve depending on project needs
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Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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