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 solutions within their Einstein Foundation team. This role is central to transforming how Salesforce enables cutting-edge, knowledge-driven experiences across their next-generation AI products. The position focuses on building next-gen Agentforce AI Agents for enterprise-wide knowledge discovery and accelerating AI with knowledge-driven context.

The Einstein Foundation team comprises an interdisciplinary mix of machine learning engineers, data scientists, and software engineers working collaboratively to build adaptive, context-aware systems. The role requires architecting and driving the development of RAG and Search solutions at scale, integrating the latest advancements in machine learning, LLMs, and vector databases.

As a Machine Learning Architect, you'll be responsible for leading the end-to-end AI lifecycle, from ideation through production, with a focus on scalable search and retrieval architectures optimized for enterprise use cases. The position requires extensive expertise in RAG platforms, semantic and vector-based search, NLP, LLMs, and knowledge graph technologies.

Key responsibilities include architecting large-scale search and retrieval solutions, innovating hybrid retrieval pipelines, optimizing system efficiency, and collaborating with cross-functional teams. The role demands 15+ years of experience in machine learning and search systems, with deep expertise in RAG platforms, vector databases, and graph-based technologies.

The position offers the opportunity to work with cutting-edge AI technologies and shape the future of enterprise AI solutions at Salesforce. You'll be working in various locations including San Francisco, Palo Alto, or Bellevue, with competitive compensation ranging from $209,700 to $384,100 depending on location.

This is a unique opportunity to make a significant impact at the intersection of AI, search technology, and enterprise solutions, working with one of the world's leading technology companies. The role requires both technical expertise and leadership skills to drive innovation in AI-driven customer success solutions.