Inference Runtime Engineer

inferact United State
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AI Summary

Inferact is seeking an Inference Runtime Engineer to optimize the execution of large language models across diverse hardware and architectures. The ideal candidate will have a deep understanding of transformer architectures and experience with LLM inference systems. The role requires strong programming skills in Python and the ability to contribute performant and maintainable code.

Key Highlights
Optimize LLM execution across diverse hardware and architectures
Work on the core of vLLM
Impact how the world runs AI inference
Technical Skills Required
Python PyTorch Transformer architectures LLM inference systems
Benefits & Perks
Generous health, dental, and vision benefits
401(k) company match
Equity
Nice to Have
Deep understanding of KV-cache memory management
Familiarity with RL frameworks and algorithms for LLMs
Contributions to open-source ML or system infrastructure projects

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 inference runtime engineer to push the boundaries of what's possible in LLM and diffusion model serving. Models grow larger. Architectures shift: mixture-of-experts, multimodal, agentic. Every breakthrough demands innovations on the inference engine itself. You'll work at the core of vLLM, optimizing how models execute across diverse hardware and architectures. Your work will directly impact how the world runs AI inference.

Skills And Qualifications

Minimum qualifications:

  • Bachelor's degree or equivalent experience in computer science, engineering, or similar.
  • Deep understanding of transformer architectures and their variants.
  • Strong programming skills in Python with experience in PyTorch internals.
  • Experience with LLM inference systems (vLLM, TensorRT-LLM, SGLang, TGI).
  • Ability to read and implement model architectures and inference techniques from research papers.
  • Demonstrate the ability to contribute performant and maintainable code and debug in complex ML codebases.

Preferred qualifications:

  • Deep understanding of KV-cache memory management, prefix caching, and hybrid model serving.
  • Familiarity with RL frameworks and algorithms for LLMs.
  • Experience with multimodal inference (audio/image/video/text).
  • Contributions to open-source ML or system infrastructure projects.

Bonus points if you have:

  • Implemented core features in vLLM or other inference engine projects.
  • Contributed to vLLM integrations (verl, OpenRLHF, Unsloth, LlamaFactory, etc).
  • Written widely-shared technical blogs or side projects on vLLM or LLM inference.

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.

Compensation Range: $200K - $400K


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