Member of Technical Staff, AMD GPU Performance Engineering

About the Company

Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware.

Responsibilities

• Build and optimize AMD GPU backends, kernels, runtime paths, and benchmarking infrastructure
• Improve performance-critical paths such as attention, GEMM, sampling, KV cache, and communication-heavy operations
• Use ROCm, HIP, Triton, CK, AITER, and related tooling to deliver frontier inference performance
• Make AMD GPU support in vLLM usable, fast, benchmarked, and maintainable

Requirements

• Bachelor's degree in computer science, engineering, systems, machine learning, or similar
• Hands-on experience optimizing AMD GPU workloads using ROCm, HIP, Triton, CK, or AITER
• Deep understanding of AMD GPU execution, memory behavior, toolchains, and kernel performance
• Experience optimizing ML kernels or inference paths (attention, GEMM, sampling, KV cache)
• Strong performance profiling and benchmarking skills using hardware counters and correctness tests

Preferred Qualifications

• Experience with vLLM, SGLang, TensorRT-LLM, or ROCm-based serving
• Familiarity with batching, KV cache, decoding, and serving tradeoffs
• Experience with compiler and kernel technologies such as Triton, MLIR, LLVM, or HIP
• Knowledge of quantization methods (INT8, FP8, mixed precision)
• Contributions to open-source ML infrastructure like vLLM, ROCm, or PyTorch