AI/ML Engineer (LLM / Generative AI

BURGEON IT SERVICES LLC
Wilmington, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Wilmington, United States of America

Tech stack

API
Artificial Intelligence
Computer Programming
Continuous Integration
Python
Machine Learning
Natural Language Processing
Performance Tuning
TensorFlow
PyTorch
Retrieval-Augmented Generation
Large Language Models
Prompt Engineering
Generative AI
Kubernetes
HuggingFace
Machine Learning Operations
Docker

Job description

We are seeking a highly experienced AI/ML Engineer with strong expertise in Large Language Models (LLMs) and Generative AI. The ideal candidate will have hands-on experience building, fine-tuning, and deploying scalable AI solutions using modern ML frameworks and cloud platforms., * Design, develop, and deploy AI/ML modelswith a focus on LLMs and Generative AI applications

  • Build and optimize NLP solutionsusing transformer-based architectures
  • Work with LLM frameworkssuch as LangChain, Hugging Face, and OpenAI APIs
  • Implement RAG (Retrieval Augmented Generation)pipelines and prompt engineering techniques
  • Fine-tune pre-trained models for domain-specific use cases
  • Collaborate with cross-functional teams to integrate AI solutions into production systems
  • Ensure scalability, performance, and reliability of ML models
  • Develop and maintain MLOps pipelinesfor continuous integration and deployment
  • Stay updated with the latest advancements in AI/ML and Generative AI

Requirements

  • 10 12 years of experience in AI/ML or Data Science
  • Strong programming skills in Python
  • Hands-on experience with LLMs, Generative AI, and NLP
  • Experience with frameworks like PyTorch, TensorFlow
  • Expertise in LangChain, Hugging Face, OpenAI, or similar tools
  • Strong understanding of Transformer models
  • Experience with RAG, fine-tuning, and prompt engineering
  • Knowledge of MLOps, Docker, Kubernetes

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