Remote HPC CUDA Engineer for Large-Scale AI

Bright Vision Technologies; Chapel Hill (NC); On-site; USD 130,000 - 180,000; Full time

Job summary

Bright Vision Technologies is seeking a highly experienced Parallel Computing Engineer with 10+ years of HPC, GPU programming, and parallel computing expertise to optimize AI, ML, and scientific workloads. Deep knowledge of CUDA, GPU architecture, distributed computing, and performance optimization is required.

The successful candidate will design scalable GPU-accelerated solutions, mentor engineers, and lead performance benchmarking across large GPU clusters, cloud environments, and enterprise

Qualifications

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline.
• 10+ years of professional experience in GPU programming, HPC, or parallel computing.
• Expert-level proficiency in CUDA C/C++, GPU architecture, and massively parallel programming techniques.
• Experience with NCCL, MPI, CUDA-aware MPI, and distributed GPU frameworks.
• Strong understanding of GPU memory hierarchy, kernel optimization, occupancy tuning, and performance analysis.
• Hands-on experience integrating custom GPU kernels into ML frameworks (PyTorch, TensorFlow, JAX).
• Strong C/C++ programming skills with debugging, profiling, and optimization.

Responsibilities

• Design, develop, and optimize CUDA kernels for AI, DL, and scientific computing.
• Profile and optimize GPU workloads using Nsight tools and CUDA profilers.
• Optimize memory management, kernel execution, and multi-GPU scaling.
• Design scalable distributed training and inference architectures using NCCL, MPI, and CUDA-aware libraries.
• Develop custom GPU operators for PyTorch, TensorFlow, JAX, Triton, or similar frameworks.
• Improve training and inference performance for large language models and AI workloads.
• Collaborate with researchers and engineers to accelerate production AI applications.
• Build benchmarking frameworks, regression testing, and optimization pipelines.
• Evaluate emerging GPU technologies and accelerator architectures for efficiency.
• Mentor engineers and provide leadership in GPU optimization and HPC.

Skills

CUDA C/C++

GPU programming

HPC

Distributed computing

Performance profiling

Multi-GPU scaling

PyTorch integration

Education

Bachelor's/Master's in CS/CE/EE

Tools

NVIDIA Nsight Systems

NVIDIA Nsight Compute

CUDA Profiler

NCCL

MPI

Job description

Bright Vision Technologies is seeking a highly experienced Parallel Computing Engineer with 10+ years of HPC, GPU programming, and parallel computing expertise to optimize AI, ML, and scientific workloads. Deep knowledge of CUDA, GPU architecture, distributed computing, and performance optimization is required.

The successful candidate will design scalable GPU-accelerated solutions, mentor engineers, and lead performance benchmarking across large GPU clusters, cloud environments, and enterprise