Remote CUDA GPU Software Engineer – HPC Performance

Bright Vision Technologies; Andover (MA); On-site; USD 100,000 - 175,000; Full time

Job summary

Bright Vision Technologies is seeking a GPU Software Engineer with deep CUDA expertise to design and optimize compute-intensive workloads on modern accelerator hardware. You will focus on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing workloads.

The role requires strong low-level systems mastery, rigorous software engineering practices, and collaboration with product, design, and engineering teams to

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field.
• Six or more years of experience in GPU programming and performance engineering.
• Deep expertise in CUDA C/C++ and GPU programming models.
• Strong understanding of modern GPU architectures, memory hierarchies, and execution models.

Responsibilities

• Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use cases.
• Profile and optimize GPU code using Nsight Systems, Nsight Compute, and CUDA profilers.
• Tune memory access patterns, occupancy, register usage, and shared memory utilization for peak performance.
• Develop highly optimized libraries for linear algebra, attention, and other ML primitives.
• Optimize multi-GPU and multi-node training using NCCL, RDMA, and high-performance networking.

Skills

CUDA programming

GPU performance engineering

C++ (modern)

GPU architecture

communication & collaboration

Education

Bachelor’s or Master’s degree in CS/CE

Tools

NCCL

MPI

Nsight Systems

Nsight Compute

Triton

Job description

Bright Vision Technologies is seeking a GPU Software Engineer with deep CUDA expertise to design and optimize compute-intensive workloads on modern accelerator hardware. You will focus on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing workloads.

The role requires strong low-level systems mastery, rigorous software engineering practices, and collaboration with product, design, and engineering teams to