Member of Technical Staff, AMD GPU Performance Engineering

INFERACT SINGAPORE PTE. LTD.; Penarth; Vor Ort; GBP 99.000 - 198.000; Vollzeit

Benefits dieser Stelle

Equity

Medical coverage

Yearly bonus

Zusammenfassung

Inferact is seeking an AMD GPU performance engineer to advance vLLM as a premier inference engine on AMD accelerators. You will build and optimize AMD GPU backends, kernels, and benchmarking infrastructure using ROCm, HIP, Triton, CK, and AITER.

You will work at the boundary of inference systems, kernels, compilers, and hardware, improving attention, GEMM, sampling, KV cache, and other communication-heavy paths to deliver fast, scalable inference and maintainable backend.

Qualifikationen

• Bachelor's degree or equivalent in CS, engineering, systems, ML, or similar.
• Hands-on experience optimizing AMD GPU workloads using ROCm, HIP, Triton, CK, AITER, or similar tools.
• Deep understanding of AMD GPU execution, memory behavior, toolchains, kernel performance, and backend constraints.
• Experience optimizing ML kernels or inference paths (attention, GEMM, sampling, KV cache, fused kernels, or heavy-communication paths).
• Strong performance profiling with measurements, hardware counters, correctness tests, and reproducible benchmarks.

Aufgaben

• Build and optimize AMD GPU backends, kernels, runtime paths, and benchmarking infrastructure using ROCm, HIP, Triton, CK, AITER, and related tooling.
• Improve performance-critical paths such as attention, GEMM, sampling, KV cache, and communication-heavy operations to enable fast, maintainable backend for vLLM.

Kenntnisse

ROCm

HIP

Triton

CK

AITER

Performance profiling

ML kernels

Ausbildung

Bachelor's degree or equivalent

Tools

vLLM

TensorRT-LLM

LLVM

MLIR

Jobbeschreibung

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, a position that took years to build.

About the Role

We're looking for an AMD GPU performance engineer to make vLLM a first-class inference engine across the AMD accelerator ecosystem. You'll 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.

You'll 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:

• Bachelor's 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.

Preferred qualifications:

• 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.

Bonus points if you have:

• 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.

Logistics

Fresh graduates are welcome to apply. Minimum years of work experience: 0.

Compensation: Monthly salary of S$15,000 to S$30,000, depending on background, skills, and experience, plus equity.

Benefits: Inferact offers a generous benefits package, including medical, dental, and vision coverage.