Top AI & Machine Learning Jobs in San Francisco, CA

Twelve-week Machine Learning Engineer internship developing, deploying, and operating production-scale ML models and pipelines. The intern will lead a research-to-production project, apply supervised, unsupervised, or reinforcement learning techniques, collaborate with engineering and product teams on blockchain and crypto use cases, and present findings to stakeholders.

The Data Science Intern will analyze data, build analytical models and datasets, support A/B tests and causal inference experiments, and deliver actionable recommendations to product and engineering teams. The role involves maintaining data pipelines, conducting analytical deep dives, and communicating insights to technical and non-technical audiences. This is a 12-week summer internship with mentorship from senior data scientists and exposure to data-driven decision-making in the crypto industry.

Architect and build production agentic AI systems for compliance automation and customer support. Lead technical direction for distributed systems, APIs, orchestration layers, guardrails, and evaluation frameworks that improve grounding and reduce hallucinations. Create reusable automation primitives, define strategic roadmaps, collaborate across teams, and mentor engineers on AI system design and production readiness.

Ownership of reliability, monitoring, and incident response for AI infrastructure. Build automation and tooling for CI/CD and Kubernetes, extend deployment frameworks, integrate security tooling, improve observability and documentation, and develop internal full-stack tools in Go or Python. Provide on-call support, lead RCA and blameless retros, and drive measurable reliability improvements.

Lead end-to-end pricing experimentation and strategy for consumer and business products: design A/B tests, build pricing and predictive models, develop production-grade data pipelines, partner with Product/Engineering/Finance, and present actionable recommendations to senior leadership.

Founding engineer building an AI-native finance automation platform: design LLM-based agents for close, reconciliation, and filings; ensure SOX-compliant, auditable agent workflows; integrate NetSuite/Workday/Anaplan and financial data pipelines; define compliance-grade engineering patterns and partner with FP&A/Treasury to translate spreadsheet workflows into production systems.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, create grounding and measurement pipelines, drive end-to-end AI projects, mentor engineers, and participate in on-call and incident response.

Lead and grow engineering teams building AI-driven automation and platform solutions (LLMs/Agentic AI) for Compliance. Own design, delivery, operations, architecture, hiring, and cross-functional collaboration to build scalable, multi-tenant distributed systems and drive AI adoption.

Architect and build a production-grade Legal AI platform of LLM-based agents and automated workflows to automate high-volume legal tasks, own institutional client agreement automation, consolidate agent tooling, define make-vs-buy strategy, and partner with legal leadership to translate workflows into scalable engineered systems.

Lead technical programs to build and scale knowledge systems powering self-service, internal tools, and AI-assisted support. Translate strategy into technical specs, APIs, schemas, and delivery plans; manage cross-functional alignment, roadmap tracking, dependency and risk management, and launch-readiness. Drive CMS, metadata, RAG/vector DB, and workflow automation initiatives to improve accuracy, machine-readability, and operational scale while reducing manual work.