Machine Learning Architect - RAG Foundations

Salesforce, the world's leading AI CRM company, is seeking a visionary Machine Learning Architect to spearhead advancements in RAG (Retrieval-Augmented Generation) solutions within their Einstein Foundation team. This role is crucial in transforming how Salesforce enables cutting-edge, knowledge-driven experiences across their next-generation AI products.

The position requires an exceptional leader with 15+ years of experience in machine learning and search systems, who will architect and drive the development of RAG and Search solutions at scale. The role involves integrating the latest advancements in machine learning, Large Language Models (LLMs), and vector databases to create enterprise-scale solutions that serve millions of users globally.

As part of the Einstein Foundation team, you'll work alongside machine learning engineers, data scientists, and software engineers in a collaborative environment focused on building adaptive, context-aware systems. The role offers the opportunity to shape the future of AI-driven customer success solutions at Salesforce.

Key responsibilities include architecting large-scale search and retrieval solutions, developing innovative hybrid retrieval pipelines, optimizing system efficiency, and leading cross-functional collaboration. The ideal candidate will have deep expertise in RAG platforms, semantic and vector-based search, NLP, LLMs, and knowledge graphs.

The position offers a competitive compensation package with a base salary range of $230,700 to $384,100 (depending on location), plus equity and comprehensive benefits. This is a hybrid role with locations in San Francisco, Palo Alto, or Bellevue, offering the flexibility to balance office and remote work.

Join Salesforce to be at the forefront of AI innovation, working with cutting-edge technologies while contributing to a company that values both business success and positive social impact. This role presents an exceptional opportunity for a technical leader to make a significant impact on the future of enterprise AI solutions.