Remote GPU Systems Engineer — CUDA & HPC Expert

Bright Vision Technologies; Oregon; Híbrido; USD 100.000 - 150.000; Jornada completa

Descripción de la vacante

Bright Vision Technologies is seeking a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware, focusing on AI training, inference, scientific computing, and high-throughput data processing. This role combines low-level systems mastery with strong software engineering practices.

You will collaborate with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into well-engineered solutions, and raise

Formación

• Six+ 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.

Responsabilidades

• 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.

Conocimientos

CUDA programming

GPU programming

C/C++

Performance engineering

HPC

Profiling

Parallel computing

Educación

Bachelor's or Master's in Computer Science/Engineering or related field

Herramientas

NCCL

MPI

Nsight Systems

Nsight Compute

CUDA profilers

TensorRT

CUTLASS

LLVM/MLIR

Descripción del empleo

Bright Vision Technologies is seeking a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware, focusing on AI training, inference, scientific computing, and high-throughput data processing. This role combines low-level systems mastery with strong software engineering practices.

You will collaborate with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into well-engineered solutions, and raise