Member of Technical Staff, Inference
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Before you apply
Salary$200k – $400k
LocationSan Francisco
Work modeon-site
Typefull-time
SeniorityMid
DepartmentResearch & Engineering
EquityIncluded
Company size51–200 people
PostedJun 18, 2026 · 4mo ago
Verified live21h ago
May no longer be actively hiring
Posted by the company on Jun 18, 202645% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
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
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
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
Skills
Python
PyTorch
vLLM
TensorRT-LLM
SGLang
TGI
Benefits
Health insurance
Dental insurance
Vision insurance
401(k)
About the company
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.
Nice to have
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.
Legal
Inferact, Inc. is an E-Verify company, and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.