Member of Technical Staff, AMD GPU Performance Engineering

MindSource is seeking aAMD GPU Performance Engineer forone of our Direct Client . If interested please drop your resume to

About the Role
Were looking for an AMD GPU performance engineer to make vLLM a first-class inference engine across the AMD accelerator ecosystem. Youll build and optimize AMD GPU backends kernels runtime paths and benchmarking infrastructure using ROCm HIP Triton CK AITER and related tooling so vLLM can deliver frontier inference performance on AMD GPUs.
Youll work at the boundary of inference systems kernels compilers and hardware architecture improving performance-critical paths such as attention GEMM sampling KV cache and communication-heavy operations. Your work will help make AMD GPU support in vLLM usable fast benchmarked and maintainable.

Skills and Qualifications
Minimum qualifications:

• Bachelors degree or equivalent experience in computer science engineering systems machine learning or similar.
• Hands-on experience optimizing AMD GPU workloads using ROCm HIP Triton CK AITER or similar AMD ecosystem tools.
• Deep understanding of AMD GPU execution memory behavior toolchains kernel performance and backend-specific performance constraints.
• Experience optimizing ML kernels or inference paths such as attention GEMM sampling KV cache fused kernels or communication-heavy runtime paths.
• Strong performance profiling and benchmarking skills with the ability to use measurements hardware counters correctness tests and reproducible benchmarks to guide optimization work.

• Experience with vLLM SGLang TensorRT-LLM ROCm-based serving or other LLM inference systems.
• Familiarity with batching KV cache decoding serving tradeoffs and backend performance constraints in production inference systems.
• Experience with compiler and kernel technologies such as Triton MLIR LLVM CK AITER HIP or other kernel DSLs and backend libraries.
• Knowledge of quantization methods such as INT8 FP8 mixed precision or AMD hardware-specific numeric formats including accuracy and performance tradeoffs.

• Contributed to vLLM ROCm HIP Triton CK AITER PyTorch compiler projects or other open-source ML infrastructure.
• Built AMD GPU benchmarking infrastructure or automated performance regression detection for accelerator workloads.
• Worked directly with AMD accelerator platform teams or early-access programs to ship backend compiler or inference performance improvements.