Join Inferact as a performance engineer to optimize vLLM, the fastest AI inference engine, working with cutting-edge hardware.
Posted by employer 7 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Not disclosed in this posting: years of experience.
Benefits
Joblaze summary
In this role, the performance engineer focuses on developing and optimizing kernels to enhance the efficiency of vLLM, ensuring it remains a leading AI inference engine. Key skills include deep expertise in CUDA and a solid grasp of GPU architecture, alongside proficiency in C++ and Python for high-performance coding. This position is ideal for experienced engineers with a background in performance optimization and a passion for benchmarking. Inferact, founded by the creators of vLLM, emphasizes collaboration with hardware vendors to maximize performance across various accelerator platforms.
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.
- 6546 active Python roles on Joblaze right now.
- 1661 active C++ roles on Joblaze right now.
- 127 active GPU roles on Joblaze right now.
- Salary band is in line with the typical range for AI/ML roles (median ~$188,000).
- Pays more than 79% of the 3239 salaried Python roles we track (median $160,000). See Python salary trends
Quick facts
- Is the Member of Technical Staff, Kernel Engineering role remote?
- It's hybrid — Inferact expects some on-site time in San Francisco.
- What's the salary range?
- Inferact lists $200,000–$400,000 for this role.
- Where is the role based?
- Inferact is hiring for this position in San Francisco.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: C++, CUDA, GPU, LLVM, ML, MLIR.
- 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, Kernel 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 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 San Francisco, California. Will consider remote in the US for exceptional candidates.
Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.
Visa sponsorship: We sponsor visas on a case-by-case basis.
Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.