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

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.

Build and maintain platform APIs and real-time, low-latency streaming speech infrastructure; support migration and integration (auth, billing, metering); harden and evolve TTS and end-to-end speech model serving; work across stack from infrastructure to platform APIs.

You will build and maintain assessment ML systems, define evaluation frameworks, and collaborate with design teams to improve language proficiency assessments.

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

Develop and implement advanced AI systems for customer support, focusing on instruction tuning and information retrieval, while driving performance improvements and automation.

Design and ship production-grade agentic LLM systems (chat/voice assistants) for customer service. Build, evaluate, and optimize LLMs and MLOps pipelines, collaborate with product and design, and advance RAG, fine-tuning, RLHF, multi-agent orchestration and evaluation tooling.

Partner with messenger platform teams to design, prototype, and deepen ChatGPT integrations. Ship code, debug API/auth/latency/quota issues, translate privacy and login constraints, produce integration guides and playbooks, and support partner launches and international rollout.

Build and maintain LLM-powered agents and automation pipelines to generate, review, and publish educational content. Integrate and optimize Skilljar and Sanity CMS, eliminate content ops bottlenecks, partner cross-functionally, and implement interactive learning components.

You will design and build LLM-powered features, integrate AI capabilities into workflows, and contribute to internal practices at a healthcare-focused company.

Lead the content layer for AI-driven customer support tools, authoring dialogue flows and maintaining AI content for optimal customer experience. Analyze performance and improve workflows, ensuring accurate and safe interactions across channels.