Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

In this role, you will deliver computer-use and browser-control products, diagnose issues, collaborate with researchers, and translate user needs into features.

The Renewals Leader will build and manage a team focused on sustaining and growing recurring revenue through strategic renewals and customer engagement in a consumption-based model.

As a Software Engineer in the RL Data team, you'll build and optimize data collection pipelines, improve quality assurance frameworks, and collaborate with domain experts to enhance AI systems, focusing on reinforcement learning tasks.

The Head of Programmatic Customer Success will define and implement strategies for customer engagement, utilizing AI to optimize customer journeys, ensuring scalable adoption without direct customer management. Responsibilities include designing programs, establishing metrics for success, experimenting to drive behavior change, and hiring a high-performance team.

The Software Engineer will develop full-stack applications for AI research teams, enhancing productivity through intuitive interfaces and rapid prototyping. Responsibilities include building infrastructure, collaborating with researchers, and mentoring other engineers.

As a Research Manager, you will lead a technical team focused on mechanistic interpretability in AI. Responsibilities include project planning, team management, and collaboration across departments to ensure faster progress on AI safety research goals.

Research Scientist will develop methods for understanding LLMs, run experiments, analyze interpretability features, and communicate results. Collaborative team science is emphasized.

The Finance Systems Integration Engineer designs and builds integrations between ERP systems and financial applications, focusing on automation and data pipeline development while ensuring system reliability and data integrity.

Oversee daily order management and provisioning for executed contracts, ensure billing matches contract terms, resolve cross-functional blockers, support month-end close and audits, document and improve quote-to-cash processes, test new product/system processes, and drive operational scaling projects.

The Research Engineer for Interpretability will implement and analyze AI research experiments, optimize workflows, build supporting tools, and enhance model safety through mechanistic interpretability methods.