Gramian Consulting
Company:
https://www.linkedin.com/company/gramian-consulting
Seniority: Mid-Senior level
Industries: IT Services and IT Consulting
Job details:
About Us
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
Role Overview
We are looking for experienced
CUDA and GPU performance engineers to analyze, profile, and optimize high-performance kernels and supporting C++ code. The role combines
CUDA optimization, GPU profiling, C++, shader development, and performance analysis across different GPU architectures. No prior AI experience is required; strong systems and GPU engineering expertise is the key requirement.
CONTRACT: Freelance contractor, paid per completed task
COMMITMENT: Flexible, based on available tasks and project demand
LOCATIONS: Fully remote - GLOBAL
PROCESS: Application review, technical assessment, and onboarding
HOURLY RATE: $60-$100/h
Responsibilities
- Analyze and optimize CUDA kernels for throughput, latency, and hardware utilization
- Profile GPU workloads to identify compute, memory, synchronization, and execution bottlenecks
- Develop and implement targeted kernel optimization strategies
- Refactor C++ and CUDA codebases for performance, maintainability, and portability
- Evaluate kernel behavior across different GPU architectures and hardware generations
- Develop or adapt shader and compute workflows using GLSL and WebGPU
- Use GPU profiling tools to validate improvements and compare performance
- Document optimization approaches, benchmarks, findings, and performance gains
- Contribute technical input to GPU architecture and performance-design discussions
- Evaluate emerging GPU programming techniques and apply relevant improvements
Requirements
- Strong professional experience with CUDA programming and GPU kernel optimization
- Advanced proficiency in C++, ideally in high-performance or systems programming environments
- Proven experience profiling and tuning GPU workloads for performance
- Hands-on experience with GPU profiling tools such as NVIDIA Nsight or comparable tools
- Strong understanding of GPU architecture, memory hierarchy, parallel execution, and synchronization
- Experience analyzing performance across different GPU hardware generations
- Hands-on experience with GLSL and/or WebGPU for shader or compute development
- Ability to document performance findings and technical decisions clearly in English
Click on Apply to know more.
