Remote AI Engineer — NLP & LLM Deployment Expert

Centific; Northern (KY); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Healthcare

Dental & Vision

401k

PTO

Job summary

Centific is seeking an AI Engineer to join a distributed team focused on NLP and large-language model projects. The role includes building and deploying state-of-the-art NLP models and creating robust APIs for model integration in production environments.

Ideal candidates bring experience with PyTorch or TensorFlow, FastAPI or similar frameworks, and familiarity with LangChain/LangGraph. Docker and Kubernetes experience is highly valued for scalable deployment.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
• Experience in developing NLP models and understanding transformer architectures.
• Proficiency in Python, Java, or C++ with strong coding practices.

Responsibilities

• Develop, fine-tune, and deploy NLP models using transformer architectures.
• Build production-ready APIs with FastAPI, Flask, or Django.
• Collaborate with product managers and data scientists to deliver NLP solutions.
• Optimize model performance and scalability in production environments.
• Monitor and improve deployed NLP models and pipelines.
• Stay updated on NLP/machine learning advancements and apply best practices.

Skills

NLP

Transformer architectures

Python

Java

C++

Strong coding practices

Communication skills

Problem-solving

Education

Bachelor’s degree in Computer Science or Engineering

Master’s preferred

PhD preferred

Tools

PyTorch

TensorFlow

FastAPI

Flask

Django

Docker

Kubernetes

LangChain

LangGraph

AutoGen

Crew AI

Job description

Centific is seeking an AI Engineer to join a distributed team focused on NLP and large-language model projects. The role includes building and deploying state-of-the-art NLP models and creating robust APIs for model integration in production environments.

Ideal candidates bring experience with PyTorch or TensorFlow, FastAPI or similar frameworks, and familiarity with LangChain/LangGraph. Docker and Kubernetes experience is highly valued for scalable deployment.