Machine Learning Engineer (Architect - Search & Knowledge Graphs)

Salesforce is seeking a visionary Machine Learning Architect to lead advancements in intelligent Search and Knowledge Graph solutions within their Einstein Foundation team. This role is crucial in redefining how they enable innovative, knowledge-driven experiences across Salesforce's next-gen AI products. The position involves architecting and driving the development of intelligent Search and Knowledge Graph solutions at scale, integrating the latest advancements in machine learning, LLMs, and vector databases.

The Einstein Foundation team is an interdisciplinary mix of machine learning engineers, data scientists, and software engineers working collaboratively to build adaptive, context-aware systems. The role requires leading the end-to-end AI lifecycle, from conceptualization through production, focusing on scalable search and retrieval architectures optimized for enterprise use cases.

Key responsibilities include architecting large-scale search and retrieval solutions, developing hybrid retrieval pipelines, optimizing system efficiency through automation, and collaborating with multi-functional teams. The ideal candidate will have extensive experience in machine learning, search systems, and knowledge graphs, with expertise in semantic and vector-based search, NLP, LLMs, and distributed systems.

This position offers the opportunity to work at the forefront of AI technology, contributing to Salesforce's groundbreaking suite of autonomous AI agents (Agentforce) that serve millions of users globally. The role combines technical leadership with innovative problem-solving, requiring both deep technical expertise and strong collaborative abilities to shape the future of enterprise AI solutions.