GPU Software Engineer

GPU Software Engineer – Kernels & Runtime

A well-funded AI accelerator startup is building a new compute platform for demanding AI workloads.

The team is looking for engineers who enjoy getting models running, understanding what limits their performance and making the underlying software faster. This role will sit within the architecture team, contributing to key decisions and requires a high level of ownership.

What you’ll work on

• Develop and optimize GPU kernels for AI operations, including attention and matrix multiplication.
• Bring models onto new hardware and resolve performance or correctness issues.
• Improve memory access, parallel execution, scheduling and hardware utilization.
• Contribute to runtime software and integration with AI frameworks.
• Profile workloads, investigate bottlenecks and validate improvements through reproducible benchmarks.
• Work directly with compiler and hardware engineers to solve problems across the stack.

What we’re looking for

• Strong C++ and practical GPU programming experience using CUDA, HIP, Triton or comparable tools.
• Understanding of GPU execution, memory hierarchies, synchronization and parallel programming.
• Evidence of building, debugging or optimizing performance-sensitive software.
• Ideally, experience with data-centre GPUs, AI workloads or accelerator systems.

Successful applicants will enjoy strong salary, benefits and meaningful equity.