Remote GPU Performance Engineer - CUDA & HPC Expert

Bright Vision Technologies; Chesterfield (MO); Remote; USD 130,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a High Performance Computing Engineer to design and optimize compute-intensive workloads on modern accelerator hardware. You will support AI training, inference, scientific computing, and data processing, delivering measurable improvements in production GPU systems.

The ideal candidate has 6+ years in GPU programming with CUDA C/C++, deep CUDA knowledge, and strong C++.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• 6+ 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.
• Hands-on experience profiling and optimizing GPU workloads in production.
• Familiarity with NCCL, MPI, and high-performance interconnect technologies.
• Experience integrating custom kernels into ML frameworks.
• Strong C++ skills and modern systems programming practices.
• Solid grounding in linear algebra and numerical methods.
• Strong communication and collaboration skills with research and engineering teams.

Responsibilities

• Design and optimize compute-intensive workloads on modern accelerator hardware.
• Collaborate with cross-functional teams to translate requirements into GPU solutions.
• Contribute to production-grade GPU software through code reviews and mentorship.

Skills

CUDA C/C++

GPU programming

Performance optimization

C++

Numerical methods

NCCL / MPI interconnects

Kernel integration into ML frameworks

Communication & collaboration

Profiling tools

Education

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

Tools

NCCL

MPI

Triton

CUTLASS

LLVM/MLIR

TensorRT

Job description

Bright Vision Technologies is seeking a High Performance Computing Engineer to design and optimize compute-intensive workloads on modern accelerator hardware. You will support AI training, inference, scientific computing, and data processing, delivering measurable improvements in production GPU systems.

The ideal candidate has 6+ years in GPU programming with CUDA C/C++, deep CUDA knowledge, and strong C++.