Remote CUDA Developer - High-Performance GPU & ML

United States Digital Space LLC; United States; Remote; USD 85,000 - 110,000; Full time

Job summary

Bright Vision Technologies is seeking a CUDA Developer with deep expertise in CUDA programming, GPU architecture, and high‑performance computing 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 successful candidate will work cross‑functionally with product, design, engineering, operations, and

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 optimize compute-intensive workloads on modern accelerator hardware.
• Extract maximum performance from GPU platforms for AI training, inference, HPC workloads.
• Collaborate with product, design, engineering, operations, and business stakeholders.
• Lead code design reviews and mentor junior engineers.

Skills

CUDA C/C++

GPU programming

Performance engineering

C++

NCCL

MPI

Kernel integration

Linear algebra

Communication skills

Education

Bachelor’s or Master’s degree in CS/CE

Tools

TensorRT

CUTLASS

LLVM/MLIR

Job description

Bright Vision Technologies is seeking a CUDA Developer with deep expertise in CUDA programming, GPU architecture, and high‑performance computing 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 successful candidate will work cross‑functionally with product, design, engineering, operations, and