Intermediate Applied Scientist (NLP)

Design, train, evaluate, and deploy language models for retrieval-augmented generation, question answering, summarization, and semantic search. Collaborate with cross-functional teams to translate research into practical, scalable NLP features for enterprise workflows. Contribute production-grade Python code using PyTorch and transformer-based frameworks; drive experiments with data-driven evaluation. Monitor model performance in production and iterate to improve robustness and relevance. Contribute to shared ML infrastructure and follow best practices across the ML lifecycle from data preparation to deployment. Apply rigorous evaluation methodologies to guide experimentation and data-driven decision making.