Performance Engineer - AI Inference Engine Optimization

inferact Singapore
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AI Summary

Inferact is seeking a performance engineer to optimize the vLLM AI inference engine for modern accelerators. The ideal candidate will have experience writing CUDA kernels and optimizing GPU architecture. The role requires a strong understanding of computer science and engineering principles.

Key Highlights
Optimize vLLM AI inference engine for modern accelerators
Write CUDA kernels and low-level optimizations
Collaborate with hardware vendors to ensure maximum performance
Key Responsibilities
Write kernels and low-level optimizations for vLLM
Work directly with hardware vendors to ensure maximum performance
Optimize code for hundreds of accelerator types
Technical Skills Required
CUDA C++ Python
Benefits & Perks
Medical, dental, and vision coverage
Equity
Visa sponsorship on a case-by-case basis
Nice to Have
Experience with ML-specific kernel optimization
Knowledge of quantization techniques
Familiarity with multiple accelerator platforms

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 a performance engineer to squeeze every FLOP out of modern accelerators. You'll write the kernels and low-level optimizations that make vLLM the fastest inference engine in the world. Your code will run on hundreds of accelerator types, from NVIDIA GPUs to emerging silicon. When hardware vendors develop new chips, they integrate with vLLM. You'll work directly with these teams to ensure we're extracting maximum performance from every generation of hardware.

Skills And Qualifications

Minimum qualifications:

  • Bachelor's degree or equivalent experience in computer science, engineering, or similar.
  • Deep experience writing CUDA kernels or equivalent (CuTeDSL, Triton, TileLang, Pallas).
  • Strong understanding of GPU architecture: memory hierarchy, warp scheduling, tiling, tensor cores.
  • Proficiency in C++ and Python with demonstrated ability to write high-performance code.
  • Experience with profiling tools (Nsight, rocprof) and performance optimization methodologies.
  • Obsession with benchmarks and squeezing every percentage point of speedup.

Preferred qualifications:

  • Experience with ML-specific kernel optimization (FlashAttention, fused kernels).
  • Knowledge of quantization techniques (INT8, FP8, mixed-precision).
  • Familiarity with multiple accelerator platforms (NVIDIA, AMD, TPU, Intel).
  • Experience with compiler technologies (LLVM, MLIR, XLA).

Bonus points if you have:

  • Kernel-related contributions to vLLM or other inference engine projects.
  • Contributions to open-source GPU, ML systems, or compiler optimization projects
  • Written deep technical blogs on GPU optimization.

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.

Compensation Range: $200K - $400K


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