Top AI & Machine Learning Jobs in San Francisco, CA

Leads Snap’s Content Machine Learning Engineering organization, setting multi-year strategy for recommendation, ranking, content understanding, reliability, and experimentation. Oversees distributed teams, develops organizational roadmaps, partners with executives and cross-functional leaders, influences scalable architecture decisions, and builds high-performing engineering teams. The role requires strong expertise in machine learning, deep learning, AI, ranking systems, and large-scale engineering leadership.

Analyze large datasets using quantitative methods, data mining, statistical modeling, and AI tools to generate actionable product and business insights. The role designs and tracks product metrics, builds dashboards and reports, identifies trends and opportunities, and supports data-driven decisions. Responsibilities include collaborating with product managers, engineers, marketers, and designers, applying statistical techniques such as A/B testing and causal analysis, and independently driving projects to completion.

Designs, scales, and leads machine learning systems that detect harmful content and bad actors, support content moderation, and promote platform integrity. Provides technical direction across the ML organization, partners with cross-functional leadership, improves ML infrastructure and operational excellence, and delivers performant, scalable models using modern deep learning techniques.

Build, deploy, and maintain machine learning models powering Snapchat products at scale. Own the full ML lifecycle from data analysis through production deployment, apply modern ML techniques, and collaborate with cross-functional teams to launch ML-driven features. Use AI tools to develop scalable services while ensuring code correctness, security, performance, and architectural quality. Mentor collaborators and solve ambiguous, large-scale problems.

Build and deploy machine learning models powering Snapchat products at scale. Own the full ML lifecycle from data analysis through production deployment, apply modern ML techniques, and collaborate with cross-functional teams to launch ML-driven features. Develop scalable, secure, production-ready services using AI-assisted engineering workflows, while contributing to ranking, recommendations, search, content understanding, or image-generation applications.

Leads experimentation, causal inference, advanced statistical analysis, machine learning, and scalable data-product development. Partners with product, engineering, and research teams to generate insights, identify opportunities, influence executive decisions, and shape product strategy. Owns cross-functional projects, analytics roadmaps, reporting, stakeholder adoption, and methodological standards while translating complex data into actionable business outcomes.

Lead and grow a team of ML and software engineers to build large-scale indexing, retrieval, and ranking systems for Snapchat ads. Define architecture and evaluation frameworks, collaborate with product and data science, measure outcomes, and raise engineering and ML standards while shaping Snap's broader ML strategy.