Top Natural Language Processing (NLP) Jobs in Los Angeles, CA

Summer internship working on transformer-based models to automate scoring of Spanish constructed responses. Collaborate with psychometricians and data scientists to design experiments, implement models in Python, evaluate with industry metrics (QWK, accuracy, SMD), and document and present findings.

Review and evaluate AI-generated responses, annotate and validate text/conversations, identify linguistic and contextual issues, and ensure annotations meet quality and linguistic guidelines to improve LLM performance.

Build and maintain full-stack, AI-native features for Cross River's data platform, including React UIs, Python APIs, LLM-powered agents, RAG, and natural-language-to-SQL experiences. Ensure secure, auditable model integration, data governance, and operational stability while collaborating across engineering and data teams.

Lead design, research, and productionization of advanced NLP and LLM systems (NER, classification, generation, RAG/GraphRAG, semantic search). Drive experiments, model evaluation, data labeling strategy, and integration of NLP models into production workflows while providing technical leadership across engineering, product, and data teams.

Design, train, and deploy high-throughput ML/NLP models and pipelines at consumer scale. Build resilient production model services, migrate ML infrastructure to public cloud (GCP), process massive distributed datasets, integrate AI-driven workflows, and collaborate cross-functionally to embed personalization into Yahoo Mail while maintaining code quality and performance.

Develop AI agents leveraging large language models, integrate external tools, and ensure production-ready AI features while collaborating across teams.

Design, build, and operate LLM-facing backend services and evaluation systems. Develop prompts, context pipelines, tool-calling workflows, and retrieval systems. Measure and improve model grounding, consistency, latency, and cost. Ship production-ready solutions and rigorous regression/evaluation pipelines for real-world therapeutic data.

Build and productionize large-scale ML models and pipelines for query understanding and personalization. Work on autocomplete, query tagging/NER, query expansion, intent modeling, and LLM-powered natural-language search. Collaborate cross-functionally to design, deploy, and monitor batch and real-time systems, leveraging modern ML infrastructure and tooling to improve search relevance across Airbnb products.

Design, fine-tune, evaluate, and deploy LLM-driven, user-facing browser features using RAG, embeddings, prompt engineering, and modern ML tooling. Lead end-to-end model lifecycle, run production experiments, collaborate with product and engineering, and document and review work with an emphasis on privacy, latency, and usability.

The NLP Scientist will solve complex medical document understanding problems using NLP and CV methodologies, optimize models for performance, and make data-driven decisions.