Member of Technical Staff, AMD GPU Performance Engineering

INFERACT SINGAPORE PTE. LTD.; Singapore; On-site; SGD 167,000 - 335,000; Full time

Benefits offered by this job

Equity

Medical insurance

Dental

Job summary

Inferact seeks 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, runtime paths, and benchmarking infrastructure to deliver frontier inference performance on AMD GPUs.

You will work at the intersection of inference systems, kernels, compilers, and hardware architecture, focusing on attention, GEMM, sampling, KV cache, and communication-heavy paths to enhance speed, reliability, and

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.

Responsibilities

• Build and optimize AMD GPU backends, kernels, runtime paths, and benchmarking infrastructure for vLLM on AMD GPUs.
• Collaborate at the boundary of inference systems, kernels, compilers, and hardware architecture to improve performance-critical paths.
• Contribute to the usability, speed, benchmarking, and maintainability of AMD GPU support in vLLM.

Education

Bachelor's degree or equivalent

Tools

ROCm

HIP

Triton

CK

AITER

Job description

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.