Zimmer Biomet seeks an NLP Engineer to design and deploy natural language processing systems that extract insights from regulatory, clinical, and operational documents. The role spans retrieval-augmented generation, document extraction, model evaluation, and production deployment on Azure, serving multiple business functions in a regulated medical device environment.

Responsibilities

Design and build retrieval-augmented generation pipelines with chunking, embedding, and reranking strategies
Develop production-ready extraction systems for unstructured documents including OCR output and complex layouts
Build and maintain evaluation harnesses measuring groundedness, factual accuracy, and system performance
Select, fine-tune, and validate language models against use-case-specific success criteria
Deploy NLP services on Azure, monitor for quality drift and cost, and support production systems

Requirements

Strong Python proficiency with PyTorch, TensorFlow, Hugging Face Transformers, spaCy, scikit-learn, pandas
Practical experience with LLM frameworks such as LangChain or LlamaIndex
Working knowledge of vector databases and embedding retrieval systems
Solid understanding of transformer architectures, tokenization, embeddings, and fine-tuning
Ability to design and evaluate NLP pipelines for accuracy, hallucination rate, and cost metrics
Experience deploying machine learning services to cloud platforms with monitoring and observability

NLP Engineer

Start with your email