Top Natural Language Processing (NLP) Jobs in San Francisco Bay Area, CA

Build and ship production LLM workflows for contract review, redlining, extraction, and legal Q&A. Design agent orchestration and multi-step reasoning pipelines, diagnose and fix model failures, work with customers to turn legal problems into reliable AI systems, and own features end-to-end from design to production.

You will build and maintain ML models, apply NLP techniques, design experiments, and partner with engineering for model deployment.

Design, implement, and productionize conversational AI models and pipelines to improve instruction following, retrieval, memory, and long-horizon task completion. Lead multi-quarter research and engineering initiatives, integrate models with platform and product teams, and translate ambiguous research ideas into measurable production milestones.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Founding clinical AI researcher bridging medicine and engineering: define clinical requirements, curate and annotate datasets, develop and validate AI/NLP/LLM models for hospital quality and patient safety, engage hospital partners, design prompts and workflows, and produce clinical documentation and validation reports for product and regulatory use.

Design, build, and productionize LLM-based conversational and AI systems for enterprise coaching. Integrate structured and unstructured data, prototype end-to-end services, improve model behavior and observability, and collaborate with product and engineering to deploy scalable, reliable AI-driven coaching workflows.

The Senior AI Engineer will design and develop voice agents and agentic workflows for healthcare operations, ensuring reliable interactions and efficient backend processes while monitoring performance and iterating on systems based on user feedback.

As an ML research engineer, you will develop systems using language models, curate datasets, set evaluation metrics, and scale semantic search processes.

Build a zero-to-one AI-native financial services app on ChatGPT Work and Codex. Design full-stack experiences, backend services, APIs and integrations with financial data and enterprise systems. Work with customers, product, research, and engineering to iterate, secure, and scale production-grade capabilities that leverage organizational memory and OpenAI models.

The Machine Learning Scientist role involves advancing small, high-performance language models, focusing on training, optimization, and evaluation. Collaboration with teams to quickly deploy breakthroughs is key.