Join Inferact as an inference runtime engineer to optimize AI model execution across diverse hardware and architectures.
Posted by employer 2 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 8 hours ago
AI in the day-to-day
You'll work at the core of vLLM, optimizing how models execute across diverse hardware and architectures.
Requirements
Not disclosed in this posting: years of experience.
Benefits
Joblaze summary
In this role, the inference runtime engineer focuses on enhancing the performance of large language models and diffusion model serving by optimizing the vLLM inference engine across various hardware setups. Key skills include a strong grasp of transformer architectures, proficiency in Python and PyTorch, and experience with LLM inference systems. This position is ideal for someone with a solid technical background, particularly in machine learning and system infrastructure, who is eager to contribute to cutting-edge AI advancements. Inferact, founded by the original creators of vLLM, is positioned at the forefront of AI inference technology.
Joblaze insights
Quick facts
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.
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.
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.
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.