Top AI & Machine Learning Jobs in San Francisco, CA

Build and deploy AI-powered tools for business and clinical teams by studying workflows, shipping production software, measuring usage and impact, and enabling teams to operate solutions independently. The role requires privacy-by-design practices because of sensitive mental healthcare data, including synthetic or masked data and separation of clinical content from operational tools. Responsibilities also include optimizing models and costs, integrating with legacy systems, and creating reusable AI building blocks.

Leads hands-on development of AI and machine learning systems for patient experiences, including matching, ranking, recommendations, onboarding, and personalization. Builds production models, shared ML infrastructure, training and inference pipelines, evaluation frameworks, and operational tooling. Partners with ML and Patient Engineering teams on architecture, experimentation, model reliability, and technical standards. Guides decisions between custom ML, foundation models, deterministic software, and hybrid solutions while mentoring engineers and driving measurable product impact.

Leads Rula’s AI Engineering team, managing Senior and Staff engineers developing applied AI features such as transcript summarization and search relevance while building ML infrastructure, feature stores, deployment systems, and observability platforms. The role requires balancing product delivery with scalable platform investments, coaching high-performing teams, and ensuring clinical safety, privacy, compliance, and rigorous AI evaluation in a regulated healthcare environment.

Analyze billing patterns, healthcare claims, and complex datasets to identify anomalies and integrity issues. Build risk-monitoring pipelines, compliance dashboards, and proactive safeguards for the Trust and Safety team. Translate technical findings into clear risk assessments for legal, compliance, and executive stakeholders while supporting regulatory compliance and protecting patient care.

Lead analytics for EHR and revenue cycle products and operations. Partner with Product, Finance, Billing, and CX to run experiments, analyze financial and operational metrics, investigate billing/account issues, and deliver actionable insights that improve accuracy, reduce friction, and support sustainable growth.