About this role
Build and optimize AMD GPU and TPU backends, kernels, and compiler integrations to make vLLM a first-class inference engine for non-NVIDIA accelerators. Improve critical inference paths including attention, GEMM, and KV-cache while developing benchmarking infrastructure.
Requires a Bachelor's degree in CS or a related field and hands-on experience optimizing workloads on AMD GPUs or TPUs using tools like ROCm or XLA. Candidates must be proficient in performance profiling and optimizing ML inference paths such as fused kernels and backend runtimes.
What they're looking for
AMD GPU OptimizationTPU Performance EngineeringROCmHIPTritonXLAJAXPallas
Frequently asked questions
What does a Member of Technical Staff, AMD GPU Performance Engineering at Inferact do?
Build and optimize AMD GPU and TPU backends, kernels, and compiler integrations to make vLLM a first-class inference engine for non-NVIDIA accelerators. Improve critical inference paths including attention, GEMM, and KV-cache while developing benchmarking infrastructure. Requires a Bachelor's degree…
What skills does this Member of Technical Staff, AMD GPU Performance Engineering role need?
Key skills for this role include AMD GPU Optimization, TPU Performance Engineering, ROCm, HIP, Triton, XLA.
How much does a Member of Technical Staff, AMD GPU Performance Engineering at Inferact pay?
The employer did not list a salary for this role. Most similar Singapore roles publish their band on the job page.
Is this Member of Technical Staff, AMD GPU Performance Engineering role remote, hybrid, or on-site?
This role is on-site, based in Singapore.
How do I apply for this Member of Technical Staff, AMD GPU Performance Engineering role?
You can apply directly on Inferact's careers page. ApplyLah can tailor your résumé and cover letter to this exact role in seconds first.