Remote CUDA Developer — GPU HPC Expert

Bright Vision Technologies; Mountain View (CA); On-site; USD 85,000 - 110,000; Full time

Job summary

Bright Vision Technologies in the United States is seeking a CUDA Developer for 100% remote work. You will design and optimize compute-intensive workloads on modern GPUs for AI training, inference, and data processing, collaborating with product, design, and engineering teams.

The ideal candidate has CUDA C/C++ expertise, deep knowledge of GPU architectures, and production profiling experience, with 6+ years in GPU programming and performance engineering.

Qualifications

• Bachelor’s or Master’s degree in CS/CE or related field.
• 6+ years of 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.
• Profiling and optimizing GPU workloads in production.
• Familiarity with NCCL, MPI, and high-performance interconnects.
• Experience integrating custom kernels into ML frameworks.
• Strong C++ skills and modern systems programming.
• Background in linear algebra and numerical methods.
• Strong communication and collaboration with research and engineering teams.

Responsibilities

• Design and optimize compute-intensive workloads on GPUs.
• Extract maximum performance from GPU platforms for AI training, inference, and high-throughput data processing.
• Collaborate with cross-functional partners to translate requirements into engineered solutions and mentor junior engineers.

Skills

CUDA C/C++

GPU programming

Performance optimization

C++

Profiling

Numerical methods

Linear algebra

Education

Bachelor’s or Master’s degree in Computer Science / Computer Engineering

Tools

NCCL

MPI

Triton

CUTLASS

TensorRT

MLIR

Job description

Bright Vision Technologies in the United States is seeking a CUDA Developer for 100% remote work. You will design and optimize compute-intensive workloads on modern GPUs for AI training, inference, and data processing, collaborating with product, design, and engineering teams.

The ideal candidate has CUDA C/C++ expertise, deep knowledge of GPU architectures, and production profiling experience, with 6+ years in GPU programming and performance engineering.