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

Build and ship end-to-end AI voice agent features across backend and frontend, own post-deployment analytics, engage users for feedback, and solve novel product and technical problems.

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.

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

The Applied AI Engineer will work with language models to create applications, manage the model alpha program with OpenAI, conduct experiments, and influence policies.

The role involves designing and implementing conversational AI systems, managing prompt orchestration, and ensuring conversational quality through advanced evaluation frameworks.

As an AI/ML Engineer, you'll design, build, and ship large scale NLP and LLM systems for classification, ranking, and content generation while collaborating with cross-functional teams.

Lead and execute research on large language models and agentic systems, running large-scale post-training experiments (SFT, RLHF, RLAIF, DPO, GRPO), building evaluation benchmarks and data synthesis pipelines, translating research into model improvements and production deployments, publishing at top venues, and mentoring researchers and engineers.

Lead end-to-end deployments of Retell's voice AI platform, guiding discovery, designing conversational workflows, building prototypes, driving technical delivery, creating ROI models, and advising executives to ensure successful production launches and adoption.

Build and prototype state-of-the-art large language models and AI assistants, take services from ideation to production, fine-tune open-source models, use LLM platforms, analyze model statistics and projections, and collaborate cross-functionally in a fast-paced hybrid Palo Alto environment.

The role involves developing AI-driven systems for healthcare, focusing on LLMs for data extraction from clinical documents and ensuring system reliability for healthcare evaluations.