Edge-to-Cloud LLM Inference Engineer

Insider, Inc.; United States; On-site; USD 100,000 - 140,000; Full time

Job summary

EnCharge AI, based in the United States, is on the lookout for an LLM Inference Deployment Engineer. This role involves optimizing and deploying large language models for high‑performance inference using advanced AI accelerators. The ideal candidate will work on LLM integration and performance tuning while developing efficient inference pipelines.

We seek someone with a Bachelor’s or Master’s in Computer Science or Electrical Engineering, with exceptional skills in model optimization and deployment frameworks like Docker and Kubernetes. Join us in pushing the boundaries of AI technology.

Qualifications

• Bachelor’s or Master’s degree in a relevant field.
• Experience in LLM inference deployment and model optimization.
• Strong expertise in frameworks like PyTorch, ONNX Runtime, and vLLM.

Responsibilities

• Deploy and optimize LLMs from libraries like HuggingFace.
• Utilize inference runtimes for efficient execution.
• Develop high-performance inference pipelines using Docker and Kubernetes.

Skills

LLM inference deployment

Model optimization

Runtime engineering

Python programming

High-level model representations

Containerized AI deployments

LLM memory optimization

Real-time LLM applications

Education

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field

Tools

Docker

Kubernetes

PyTorch

ONNX Runtime

vLLM

TensorRT‑LLM

DeepSpeed

Triton Inference Server

TensorFlow Serving

TorchServe

Job description

EnCharge AI, based in the United States, is on the lookout for an LLM Inference Deployment Engineer. This role involves optimizing and deploying large language models for high‑performance inference using advanced AI accelerators. The ideal candidate will work on LLM integration and performance tuning while developing efficient inference pipelines.

We seek someone with a Bachelor’s or Master’s in Computer Science or Electrical Engineering, with exceptional skills in model optimization and deployment frameworks like Docker and Kubernetes. Join us in pushing the boundaries of AI technology.