Join Inferact as an AMD GPU performance engineer to optimize vLLM for the AMD accelerator ecosystem.
Posted by employer 2 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
AI in the day-to-day
vLLM is positioned as the world's AI inference engine, focusing on making inference cheaper and faster.
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Not disclosed in this posting: years of experience.
Benefits
Joblaze summary
In this role, the AMD GPU performance engineer focuses on enhancing the vLLM inference engine by optimizing AMD GPU backends and performance-critical paths. Key skills include hands-on experience with ROCm, HIP, and Triton, along with a deep understanding of GPU execution and memory behavior. This position is ideal for someone with a strong background in computer science or engineering, particularly those experienced in machine learning optimizations. The team is composed of experts in AI inference, aiming to push the boundaries of performance on AMD hardware.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Inferact's career page.
- Inferact has 24 other open roles including HR / People Lead, Head of Legal, Inference Engineering, Co-op.
- 127 active GPU roles on Joblaze right now.
- 52 active vLLM roles on Joblaze right now.
- 48 active Triton roles on Joblaze right now.
- Pays more than 17% of the 69 salaried GPU roles we track (median $198,000).
Quick facts
- Is the Member of Technical Staff, AMD GPU Performance Engineering role remote?
- No — this is an on-site role in Singapore.
- What's the salary range?
- Inferact lists SGD 200,000–SGD 400,000 for this role.
- Where is the role based?
- Inferact is hiring for this position in Singapore.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AITER, AMD, CK, GPU, HIP, ROCm.
- Does Inferact sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Inferact targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Member of Technical Staff, AMD GPU Performance Engineering role at Inferact.
From the original posting
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
Location: This role is based in Singapore.
Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is S$200,000 to S$400,000 annually + equity.
Visa sponsorship: We sponsor visas on a case-by-case basis.
Benefits: Inferact offers a generous benefits package, including medical, dental, and vision coverage.