Top AI & Machine Learning Jobs in San Francisco, CA

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Analyzes workforce and healthcare data to identify trends, build predictive and machine learning models, and deliver actionable recommendations. Uses Python, Alteryx, and Power BI for analytics, visualization, and reporting. The role supports workforce strategy, employee engagement, organizational effectiveness, talent management, and healthcare cost insights. Responsibilities also include client collaboration, relationship management, team guidance, and applying risk adjustment and medical economics concepts to inform strategic decisions.

Lead design and implementation of data architecture and scalable storage solutions, drive AI/GenAI thought leadership, oversee data governance and security, translate business requirements into technical plans, implement FastAPI endpoints, enhance LLMs through prompt engineering, and manage cross-functional teams to deliver advanced data and AI solutions.

Lead and manage data and analytics initiatives for M&A and transactions, directing teams to build ML models, dashboards, and integrated data solutions using analytics and visualization tools, ensuring data quality, stakeholder alignment, and actionable insights to drive deal decisions.

Lead analytics for M&A deals by building scalable data pipelines, applying ML and generative AI for due diligence and forecasting, automating reporting, visualizing insights, mentoring junior staff, and advising Private Equity clients to drive investment and portfolio value creation.

Develop and optimize AI and machine learning algorithms, models, and scalable Python systems. Transform raw data into actionable insights, apply machine learning libraries and NLP techniques, improve data quality, and deliver automation solutions for clients. The role also involves complex data analysis, stakeholder collaboration, client relationship management, and navigating ambiguous business challenges.

Lead and coach teams to design, develop, and deliver production-grade AI and data solutions for clients. Manage client accounts, ensure quality and timelines, analyze complex datasets, implement best practices, and drive continuous improvement while fostering client relationships and technical excellence.