Top AI & Machine Learning Jobs in San Francisco, CA

Design and implement security controls for LLMs and generative AI systems. Conduct threat modeling, architecture reviews, and vulnerability remediation for ML pipelines. Secure training, fine-tuning, and inference infrastructure, including containers, Kubernetes, and cloud/GPU environments. Develop policies, runbooks, and training; evaluate vendor AI services; assist with proofs-of-concept and incident response for AI-specific threats like prompt injection and model poisoning.

Lead design and deployment of AI-driven capabilities for Professional Services, building agentic workers, RAG/LLM-based guidance, and automation across data migration, project management, and implementation. Create AI playbooks, drive adoption and change management, optimize quality and speed, and collaborate with Product and Engineering to align internal AI tools with the product roadmap.

Join the IT AI Automation team to build and harden micro-apps and AI integrations on a governed GCP platform. Contribute to bug fixes, small features, code and design reviews, monitoring, and apply foundational software development and security practices. Gain hands-on experience with Python, SQL, CI/CD, and AI tools while supporting deployments, secrets management, testing, and documentation.

Lead intake, roadmap, and governance for an internal AI automation/platform team. Harden and operationalize business-built AI apps on a shared GCP platform, define quality and responsible-AI standards, run buy-vs-build decisions, manage stakeholders, drive adoption, and measure outcomes and AI economics.

Build, harden, deploy, and operate LLM-powered micro-apps and agents on a governed GCP platform. Integrate AI with business systems (Salesforce, Slack, NetSuite), implement CI/CD, secrets and identity controls, monitoring, and automated maintenance. Create retrieval pipelines, evaluation and observability for model quality, and partner with stakeholders to move proofs of concept into production.

Lead AI-powered product development for EZLynx's SaaS insurance platform. Define strategy and roadmap, partner with engineering and data science to build and iterate on agentic workflows and AI features, conduct user research and experiments, manage backlog and releases, measure product performance, and drive go-to-market and adoption across cross-functional teams.

Lead strategy and delivery of AI-powered, agentic features for a SaaS insurance product. Define roadmaps, validate hypotheses through research and experiments, collaborate with engineering and data science, track KPIs and ROI, drive go-to-market and adoption, mentor junior PMs, and prioritize backlog to maximize customer value and retention.