GPU Kernel Engineer: Performance-Driven ML

Mindbeam; United States; On-site; USD 100,000 - 140,000; Full time

Job summary

Mindbeam is seeking a talented GPU Programmer to enhance AI infrastructure. In this role, you will design custom GPU/accelerator kernels, optimize ML workloads, and work with researchers on efficient code solutions.

The ideal candidate holds a degree in Computer Science or similar and possesses 2+ years in GPU programming with strong skills in C++ and CUDA. Join us to push the boundaries of AI performance!

Qualifications

• 2+ years of experience in GPU programming, parallel computing, or systems-level optimization.
• Strong coding skills in C++, CUDA, or similar languages.
• Experience optimizing workloads for distributed and heterogeneous compute environments.

Responsibilities

• Design and implement custom GPU/accelerator kernels to maximize performance.
• Profile, benchmark, and optimize critical ML workloads.
• Collaborate with researchers to translate algorithmic advances into efficient, production-ready code.

Skills

GPU programming

Parallel computing

C++

CUDA

Education

Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or related field

Tools

Profiling tools

ML frameworks

Job description

Mindbeam is seeking a talented GPU Programmer to enhance AI infrastructure. In this role, you will design custom GPU/accelerator kernels, optimize ML workloads, and work with researchers on efficient code solutions.

The ideal candidate holds a degree in Computer Science or similar and possesses 2+ years in GPU programming with strong skills in C++ and CUDA. Join us to push the boundaries of AI performance!