Machine Learning Engineer (Agentic Search & Knowledge Graphs)

Salesforce is seeking a visionary Machine Learning Engineer to lead advancements in agentic Search and Knowledge Graph solutions within their Einstein Foundation team. This role is part of Salesforce's groundbreaking Agentforce suite, focusing on autonomous AI agents that enhance employee capabilities across service, sales, marketing, and commerce.

The position involves working with the Einstein Foundation team, an interdisciplinary group of machine learning engineers, data scientists, and software engineers. The role focuses on developing agentic Search and Knowledge Graph solutions at scale, integrating cutting-edge advancements in machine learning, LLMs, and vector databases.

Key responsibilities include architecting large-scale search and retrieval solutions, developing intelligent retrieval pipelines, and optimizing search systems. The ideal candidate will have extensive experience with machine learning, search systems, and knowledge graphs, along with expertise in semantic and vector-based search, NLP, and LLMs.

This is an opportunity to shape the future of AI-driven enterprise solutions at the world's leading CRM company. The role offers the chance to work on innovative technologies that serve millions of users globally, collaborating with cross-functional teams to deliver groundbreaking AI experiences.

The position requires strong technical skills in Python, distributed systems, and machine learning frameworks, combined with excellent communication abilities. Additional preferred skills include experience with multi-stage retrieval pipelines, graph embedding, and knowledge graph curation.