Remote GPU Systems Engineer: CUDA HPC & Performance

Bright Vision Technologies; South Jordan, Draper (UT, UT); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a GPU Systems Engineer 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, and HPC workloads, collaborating with cross-functional teams to translate requirements into engineered solutions.

The ideal candidate has deep CUDA programming and GPU architecture expertise, 6+ years of experience, and a track record of shipping

Qualifications

• Six or more 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.
• Hands-on experience profiling and optimizing GPU workloads in production.
• Experience integrating custom kernels into ML frameworks.
• Strong C++ skills and familiarity with modern systems programming practices.
• Strong communication and collaboration skills with research and engineering teams.

Responsibilities

• Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use cases.
• Profile and optimize GPU code using tools such as 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.
• Implement custom operators and fused kernels in PyTorch, JAX, or Triton.
• Collaborate with ML engineers to identify performance bottlenecks in training and inference pipelines.
• Develop benchmarks and regression tests to safeguard performance over time.
• Evaluate new GPU architectures and feature sets, and advise on adoption strategy.
• Contribute to compiler-level optimizations for tensor programs where appropriate, working at the boundary between ML frameworks and underlying accelerator codegen to unlock performance not reachable through framework-level tuning alone.
• Optimize memory hierarchy usage across HBM, L2, shared memory, and registers.
• Implement mixed-precision and quantized compute paths that maximize accelerator throughput while preserving numerical fidelity within bounds acceptable for the target workloads.
• Document performance characteristics, design decisions, and tuning playbooks for internal teams.
• Stay current with GPU architecture, CUDA evolution, and emerging accelerator technologies.

Skills

CUDA programming

GPU performance

Parallel computing

C++ programming

Team communication

Education

Bachelor’s or Master’s in CS/CE

Tools

Nsight Systems

Nsight Compute

CUDA profilers

NCCL

MPI

PyTorch

JAX

Triton

Job description

Bright Vision Technologies is seeking a GPU Systems Engineer 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, and HPC workloads, collaborating with cross-functional teams to translate requirements into engineered solutions.

The ideal candidate has deep CUDA programming and GPU architecture expertise, 6+ years of experience, and a track record of shipping