Remote GPU Systems Engineer (CUDA & HPC)

Bright Vision Technologies; Sammamish (WA); On-site; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies seeks a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware, focusing on AI training, inference, and HPC.

The role emphasizes deep CUDA programming expertise, strong understanding of GPU architectures, and a track record of production performance improvements. This is a fully remote, direct‑hire position with growth potential.

Qualifications

• 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.
• 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 familiarity with 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 implement high‑performance CUDA kernels for AI and HPC workloads.
• Profile and optimize GPU code using Nsight and CUDA profilers.
• Tune memory access, occupancy, and shared memory for peak performance.
• Develop optimized libraries for linear algebra and ML primitives.
• Enable multi‑GPU and multi‑node training with NCCL and high‑speed interconnects.
• Implement kernels in PyTorch, JAX, or Triton and integrate into ML workflows.
• Collaborate with ML engineers to identify and fix perf bottlenecks.
• Develop benchmarks and regression tests to safeguard performance.
• Evaluate new GPU architectures and advise on adoption strategies.
• Contribute to compiler optimizations for tensor programs where applicable.
• Document performance characteristics and tuning playbooks for teams.
• Stay current with CUDA evolution and accelerator technologies.

Skills

CUDA programming

GPU architecture

Performance optimization

Profiling tools

C++

Distributed training

NCCL/MPI

ML frameworks integration

Education

Bachelor’s or Master’s in CS/CE or related field

Tools

NCCL

MPI

TensorRT

Triton

CUDA Toolkit

Job description

Bright Vision Technologies seeks a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware, focusing on AI training, inference, and HPC.

The role emphasizes deep CUDA programming expertise, strong understanding of GPU architectures, and a track record of production performance improvements. This is a fully remote, direct‑hire position with growth potential.