CUDA Engineering Expert

CUDA Engineering Expert
- GPU Optimization Job Snapshot Role: CUDA Engineering Expert
- GPU Optimization

Location:
Abu Dhabi Emirate, United Arab Emirates Industry: Computer Software Function: IT-Software Development

Experience:
Advanced experience in CUDA, C , GPU programming, and kernel optimization

Job Type
Contractor Position Overview CUDA Engineering Expert
- GPU Optimization in Abu Dhabi Emirate, United Arab Emirates is a remote Computer Software opportunity for an experienced GPU engineer specializing in CUDA programming, advanced C development, kernel optimization, and high-performance computing. YO IT Consulting is hiring a technical expert to profile GPU workloads, eliminate performance bottlenecks, optimize compute kernels, develop shader logic, and contribute to an advanced GPU optimization project where deep engineering expertise is more important than previous AI experience.

Job Details

Country: United Arab Emirates City: Abu Dhabi Emirate Industry: Computer Software Function: IT-Software Development

Salary:
25000-45000 Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer. Gender: Any Candidate Nationality: Any

Job Type
Contractor Role Context

The CUDA Engineering Expert will investigate how kernels execute, locate memory and compute constraints, and implement targeted improvements across CUDA and C code. The work also extends into GLSL and WebGPU shader development, giving the engineer responsibility for improving both computational efficiency and the technical quality of GPU-oriented software.

Key Responsibilities

Analyze CUDA kernels and GPU workloads to determine where computational resources, memory behavior, or execution patterns are limiting performance. Profile GPU applications using NVIDIA Nsight or comparable performance analysis tools. Identify kernel-level bottlenecks and formulate optimization strategies based on measured performance data. Refactor CUDA and C implementations to improve execution efficiency, maintainability, and scalability.

Optimize GPU kernels with consideration for memory access patterns, thread organization, synchronization, occupancy, and computational throughput. Compare performance characteristics across workloads and recommend architecture-appropriate optimization techniques. Develop and refine shader logic using GLSL and WebGPU for GPU-based compute or graphics workloads. Investigate performance regressions and isolate their underlying technical causes.

Benchmark optimization changes and quantify improvements using appropriate profiling and performance metrics. Document profiling methodology, engineering decisions, bottlenecks, implemented changes, and resulting performance gains. Participate in technical discussions covering GPU architecture, kernel behavior, performance engineering, and accelerated computing. Collaborate remotely with engineering and cross-functional project teams while communicating complex optimization findings clearly. Apply consistent engineering standards when reviewing or improving performance-critical GPU code. Ideal Profile

Deep practical expertise in NVIDIA CUDA programming and GPU kernel optimization. Advanced C development skills, particularly for performance-sensitive or compute-intensive software. Hands-on experience with GLSL and WebGPU. Strong command of GPU profiling and debugging tools such as NVIDIA Nsight. Detailed understanding of GPU architecture, parallel execution, memory hierarchies, and performance characteristics. Proven ability to diagnose performance bottlenecks using profiling evidence rather than assumptions.

Experience optimizing GPU workloads for throughput, latency, resource utilization, or memory efficiency. Background in high-performance computing or GPU-accelerated applications is highly relevant. Experience tuning workloads across different GPU architectures is advantageous. Exposure to graphics programming, compute shaders, or AI and machine learning acceleration is beneficial.

Strong analytical reasoning and technical problem-solving skills. Able to document complex performance engineering work with precision and collaborate effectively in a distributed environment. Prior artificial intelligence experience is not required.

Skills

Set

NVIDIA CUDA CUDA C Advanced C GPU programming GPU kernel optimization NVIDIA Nsight GPU profiling GPU architecture Parallel computing High-performance computing Kernel performance analysis Memory optimization Thread optimization GPU occupancy analysis Performance benchmarking Compute shaders GLSL WebGPU Shader development GPU-accelerated applications Performance bottleneck analysis Cross-architecture optimization AI and machine learning acceleration Technical performance documentation Why Join Us

This contractor opportunity places advanced GPU engineering expertise at the center of a technically demanding optimization project. Engi