Machine Learning Engineer (Agentic Search & Knowledge Graphs)

World's #1 AI CRM company providing enterprise-wide AI solutions and autonomous agents
$184,000 - $384,100
Machine Learning
Senior Software Engineer
In-Person
5,000+ Employees
5+ years of experience
AI · Enterprise SaaS

Description For Machine Learning Engineer (Agentic Search & Knowledge Graphs)

Salesforce is seeking a visionary Machine Learning Engineer to spearhead the development of agentic Search and Knowledge Graph solutions within their Einstein Foundation team. This role is part of Salesforce Research and focuses on building next-generation Generative AI platforms for enterprise-wide knowledge discovery and context-driven AI systems.

The position sits within the Einstein Foundation team, which comprises a diverse group of machine learning engineers, data scientists, and software engineers. The team is dedicated to developing adaptive, context-aware systems that enhance customer interactions and insights at scale.

As a Machine Learning Engineer, you'll be responsible for driving the development of large-scale search and knowledge graph solutions, integrating cutting-edge advancements in machine learning, LLMs, and vector databases. The role requires expertise in architecting end-to-end AI lifecycles, from conception to production, with a focus on enterprise-scale search and retrieval architectures.

Key responsibilities include architecting sophisticated search and knowledge graph solutions, developing intelligent retrieval pipelines, optimizing search systems through automation, and collaborating with cross-functional teams. The role requires deep expertise in semantic and vector-based search, NLP, LLMs, and knowledge graph technologies.

The ideal candidate will have 5+ years of experience in machine learning and search systems, with strong programming skills in Python and expertise in distributed systems. They should be comfortable working with various technologies including vector databases, graph databases, and machine learning frameworks.

This position offers the opportunity to work at the forefront of AI innovation, contributing to Salesforce's recently unveiled Agentforce suite of autonomous AI agents. The role combines technical expertise with leadership, requiring both hands-on development skills and the ability to guide technical discussions and innovation in the field of search and knowledge graphs.

Working at Salesforce, you'll be part of the world's #1 CRM company, with the chance to impact millions of users globally through innovative AI solutions. The position offers competitive compensation and the opportunity to work with cutting-edge technologies in an environment that values continuous innovation and cross-functional collaboration.

Last updated 4 days ago

Responsibilities For Machine Learning Engineer (Agentic Search & Knowledge Graphs)

  • Lead the architecture of sophisticated search and knowledge graph solutions
  • Develop intelligent retrieval pipelines combining semantic, vector, and symbolic search
  • Optimize and automate search systems through demand forecasting and monitoring
  • Collaborate with cross-functional teams for AI-driven product innovation
  • Guide discussions on emerging technologies in vector search and graph embeddings

Requirements For Machine Learning Engineer (Agentic Search & Knowledge Graphs)

Python
Kafka
  • 5+ years experience in Machine Learning & Search Systems
  • Expertise in Semantic and Vector-Based Search
  • Strong Background in NLP & LLMs
  • Sophisticated Knowledge Graph Skills
  • Proficiency in Distributed Systems & ML Frameworks
  • Programming Mastery in Python & Graph Based Frameworks
  • Experience with Multi-Stage Retrieval Pipelines
  • Graph Embedding & Contextual Retrieval Expertise
  • Knowledge Graph Curation & Ontology Management

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