Senior Software Lead (Remote - US), Software Development

Hexagon Metrology • Madison, WI

260d • Remote

About The Position

Hexagon's Asset Lifecycle division (Hexagon) is seeking a Senior AI Developer with deep expertise in Retrieval-Augmented Generation (RAG) systems and prompt engineering to drive the development of cutting-edge AI applications. The ideal candidate will have extensive experience designing, optimizing, and fine-tuning AI models, with a strong focus on developing RAG-based architectures. Additionally, they should be proficient in Python and skilled in fine-tuning large language models (LLMs), vector databases, and AI pipeline optimization.

Requirements

• 5+ years of experience in AI/ML development with a focus on RAG systems and LLM applications.
• Strong expertise in prompt engineering and LLM customization for high-quality AI outputs.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
• Hands-on experience with Hugging Face Transformers, OpenAI APIs, LangChain, and LlamaIndex.
• Experience with fine-tuning LLMs using LoRA, PEFT, and full fine-tuning techniques.
• Deep understanding of vector databases (e.g., FAISS, Pinecone, Weaviate) and retrieval strategies.
• Knowledge of cloud-based AI deployments (AWS) and MLOps best practices.
• Strong understanding of NLP concepts, attention mechanisms, and self-supervised learning.
• Ability to collaborate with cross-functional teams.

Nice To Haves

• Experience with Open Source LLMs.
• Knowledge of graph-based retrieval and knowledge graphs for enhanced AI reasoning.
• Familiarity with LLM security best practices and adversarial prompt defense techniques.
• Contributions to open-source AI projects or research publications in NLP/LLMs.

Responsibilities

• Design and optimize prompts for LLMs in RAG-based systems to enhance response accuracy and relevance.
• Implement prompt chaining, dynamic prompt creation, and context-aware prompting techniques.
• Analyze LLM outputs and iterate on prompt design for better performance.
• Fine-tune retrieval strategies and improve the integration of LLMs with vector databases (e.g., FAISS, ChromaDB, Pinecone).
• Develop and fine-tune LLMs, transformers, and other NLP models for custom AI applications.
• Train and optimize models using transfer learning, LoRA, PEFT, and other fine-tuning techniques.
• Implement data augmentation and preprocessing pipelines to improve training data quality.
• Work with Hugging Face models, OpenAI APIs, and other LLM frameworks to customize and deploy AI solutions.
• Design and implement scalable AI pipelines for real-world applications.
• Optimize model performance through quantization, pruning, and model distillation.
• Work with APIs, microservices, and cloud platforms (AWS, GCP, Azure) for AI deployment.
• Develop MLOps workflows for continuous model improvement and deployment.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Computer and Electronic Product Manufacturing
• Education Level: Bachelor's degree