Remote HPC Engineer - CUDA & GPU Performance Expert

Bright Vision Technologies

Overland Park (KS)

Remote

USD 130,000 - 150,000

Full time

3 days ago
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Job summary

Bright Vision Technologies is seeking a High Performance Computing Engineer with deep CUDA programming, GPU architecture, and HPC expertise to design and optimize compute-intensive workloads on modern accelerator hardware. This role focuses on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing workloads.

The ideal candidate combines low-level systems mastery with strong software engineering practices, and has a

Qualifications

  • Bachelor’s or Master’s degree in CS/CE or related field.
  • 6+ years of GPU programming and performance engineering experience.
  • Deep expertise in CUDA C/C++ and GPU programming models.
  • Strong understanding of modern GPU architectures and memory hierarchies.
  • Experience profiling and optimizing GPU workloads in production.
  • Experience with NCCL and MPI for high-performance interconnects.
  • Strong C++ skills and systems programming.
  • Experience integrating custom kernels into ML frameworks.
  • Excellent communication and collaboration with cross-functional teams.

Responsibilities

  • Design and optimize compute-intensive workloads on modern accelerator hardware.
  • Extract maximum performance from GPU platforms for AI training and HPC workloads.
  • Collaborate with product, design, engineering, and operations teams.
  • Mentor junior engineers and participate in code/design reviews.

Skills

GPU programming
CUDA C/C++
GPU architectures
Memory hierarchies
Profiling & optimization
NCCL/MPI
ML kernel integration
C++ advanced
Linear algebra
Collaboration

Education

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

Tools

NCCL
MPI
GPU interconnects

Job description

Bright Vision Technologies is seeking a High Performance Computing Engineer with deep CUDA programming, GPU architecture, and HPC expertise to design and optimize compute-intensive workloads on modern accelerator hardware. This role focuses on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing workloads.

The ideal candidate combines low-level systems mastery with strong software engineering practices, and has a

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