Top AI Research Jobs in San Francisco Bay Area, CA

Lead and scale RingCentral's AI and systems integrator partner ecosystem end-to-end: executive relations, alliance strategy, GTM and offer strategy, partner marketplaces, field enablement, pipeline governance, cross-functional interlock, co-sell, and joint customer success while managing the AI & SI Alliances team.

The Fraud Strategy Lead will manage strategic fraud initiatives, partner with teams to enhance fraud tools, and mentor junior members, all while advancing fraud capabilities aligned with company objectives.

The role involves conducting empirical research on AI's economic effects, developing methodologies for measurement, and translating findings into policy recommendations. The economist will work cross-functionally and maintain relationships with research partners.

The Transformative AI Research Economist will develop macroeconomic models and forecasting tools to assess the impact of AI on economic scenarios, leveraging unique data from the Anthropic Economic Index to ground projections in observable trends.

As a Research Engineer, you will build and maintain data infrastructure to analyze AI's economic impact, collaborate with cross-functional teams, and ensure data integrity and privacy compliance.

The job involves leading AI research and engineering projects, developing large-scale models, collaborating with teams, and contributing to groundbreaking AI applications.

The Senior Scientist, Bio AI will leverage AI and bioinformatics to design novel genetic medicines and analyze experimental datasets, contributing to cancer diagnostics and treatment development.

Lead development of digital pathology AI models using whole-slide image data to predict clinical outcomes and morphologic features. Drive dataset selection and annotation, coordinate and mentor junior scientists, partner with bioinformatics, statistics, and clinical experts, produce analyses and visualizations for publication, and manage cross-team project execution to build diagnostic products.

Lead forward-looking research on robot learning, hardware, supply chains, and commercialization. Produce reports, forecasts, and briefings; track mobile manipulators, quadrupeds, cobots, and autonomous vehicles; assess AI, edge compute, and simulation impacts; collaborate with cross-sector analysts; support investors, OEMs, and policy stakeholders; and present findings to senior executives and clients.

Build first-principles performance and cost models for AI training and inference across chips, accelerators, memory, interconnects, racks, and datacenters. Evaluate architectures, validate models against benchmarks, analyze semiconductor manufacturing and packaging impacts on performance and cost, publish research, and advise clients and investors on hardware trade-offs and TCO metrics.

Conduct research on AI tokenomics by evaluating model architecture trends, building simulation models for training and inference efficiency across hardware and workloads, diligencing companies using model tokens, and forecasting economic impacts for investors, corporates, and policymakers.

Engram builds models that create compact, personal "engrams" (memories) to make AI context-aware and efficient. This posting invites interested candidates to submit an expression of interest for future roles or opportunities.

Join a research and advisory pipeline for an asset-management startup building an auditable reasoning engine. Advise on agentic AI, world models, interpretability, and systemic risk. Help shape research direction, identify failure modes and guardrails, and provide scholarly evidence (papers, GitHub, Google Scholar) and a short written response to demonstrate expertise.

Lead a research team focused on enhancing large-scale machine learning models' efficiency and performance, developing novel algorithms and collaborating with engineering teams to implement breakthroughs.