Member of Technical Staff, Inference

Inferact; San Francisco (CA); Hybrid; USD 200,000 - 400,000; Full time

Benefits offered by this job

Health, dental, and vision benefits

401(k) company match

Visa sponsorship on case-by-case basis

Job summary

Inferact is seeking an inference runtime engineer to enhance the performance and capabilities of LLM and diffusion model serving. This role requires expertise in optimizing model execution on various hardware architectures and has significant implications for AI inference.

The ideal candidate must possess a bachelor's degree in computer science or related fields, strong programming skills in Python, and experience with LLM inference systems. Remote work options are available for exceptional candidates.

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 from research papers.

Responsibilities

• Push the boundaries of inference model serving.
• Optimize how models execute across diverse hardware.
• Directly impact how the world runs AI inference.

Skills

Programming skills in Python

Deep understanding of transformer architectures

Experience with LLM inference systems

Ability to read model architectures

Education

Bachelor's degree or equivalent experience

Tools

PyTorch

TensorRT-LLM

vLLM

Job description

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.