Remote CUDA HPC Engineer—GPU Performance & ML Inference

Bright Vision Technologies; Flower Mound (TX); On-site; USD 130,000 - 150,000; Full time

Benefits offered by this job

Remote work

Job summary

Bright Vision Technologies is seeking a High Performance Computing Engineer with deep expertise in CUDA programming, GPU architecture, and HPC 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, and scientific computing.

The ideal candidate will work closely with product, design, engineering, and operations teams to translate ambiguous requirements into robust,

Qualifications

• Bachelor’s or Master’s degree in CS/CE or related field.
• Six or more years in GPU programming and performance engineering.
• Deep expertise in CUDA C/C++ and GPU programming models.
• Strong understanding of modern GPU architectures, memory hierarchies, 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.
• 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 GPU hardware.
• Translate ambiguous requirements into well-engineered solutions with cross-functional partners.
• Mentor junior engineers and participate in design/code reviews.

Skills

CUDA C/C++

GPU programming

Performance engineering

C++

Profiling

Numerical methods

Communication

Education

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

Tools

NCCL

MPI

TensorRT

Job description

Bright Vision Technologies is seeking a High Performance Computing Engineer with deep expertise in CUDA programming, GPU architecture, and HPC 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, and scientific computing.

The ideal candidate will work closely with product, design, engineering, and operations teams to translate ambiguous requirements into robust,