LLM Inference Engineer
Read straight from Near AI's careers page, verified 2d ago.Seekless can tailor your résumé to it.
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Before you apply
SalaryNo pay range posted
LocationGlobal - Remote, San Francisco or Remote
Work moderemote · United States
SenioritySenior
DepartmentNear AI
Company size1+ people
PostedJul 6, 2026 · 4mo ago
Verified live2d ago
May no longer be actively hiring
Posted by the company on Jul 6, 2026No pay range listed, though California requires one
At a glanceSummarised by Seekless from the posting.
Strong hands-on experience in LLM inference, with expertise debugging and optimizing major inference engines such as SGLang, vLLM, or TensorRT
Deep knowledge of state-of-the-art GPU architectures, and effectively exploit them using PyTorch, Triton, CuTe, CUDA, etc.
Proven track record in designing and maintaining end-to-end high-traffic LLM serving systems
Strong problem-solving skills
Ability to communicate technical ideas clearly
Experience with Trusted Execution Environments (TEE)
Active contributor to open-source LLM inference engines
Skills
SGLang
vLLM
TensorRT
PyTorch
Triton
CuTe
CUDA
Locations: San Francisco or Remote
About The Role
The NEAR AI team is building decentralized and confidential machine learning infrastructure to enable user-owned AI. Our mission is to build highly scalable and efficient infrastructure for open-source AI at a global scale.
We are specifically seeking an expert in high-performance LLM serving systems and inference optimization. In this role, you will push the boundaries of how large language models are served.
What You’ll Be Doing
•
Architect and maintain production high-traffic LLM serving systems.
•
Optimize throughput, latency, and cost for leading open-source LLMs.
What We’re Looking For
•
Strong hands-on experience in LLM inference, with expertise debugging and optimizing major inference engines such as SGLang, vLLM, or TensorRT.
•
Deep knowledge of state-of-the-art GPU architectures, and effectively exploit them using PyTorch, Triton, CuTe, CUDA, etc.
•
Proven track record in designing and maintaining end-to-end high-traffic LLM serving systems.
•
Strong problem-solving skills and ability to communicate technical ideas clearly.
Nice to have
We’d Love If You Have
•
Experience with Trusted Execution Environments (TEE).
•
Active contributor to open-source LLM inference engines.
Please let us know if you require any special requirements for your interview and we’ll do our best to accommodate.