Staff Machine Learning Engineer - Knowledge Graph

Directors
  • San Francisco
  • Permanent
  • Permanent IT
  • ABo14-1624765
  • 14/10/2025
Staff Machine Learning Engineer – Knowledge Graph
Hybrid – San Francisco, CA
$250,000–$350,000 + Excellent Benefits


We’re partnered with a pioneering technology company redefining how enterprises manage, transform, and leverage data in the age of AI. Their platform sits at the intersection of large-scale data engineering and advanced AI, powering innovation across industries such as banking, healthcare, life sciences, and technology.


As a Staff Machine Learning Engineer – Knowledge Graph, you’ll play a leading role in building and scaling intelligent graph systems that enhance retrieval, reasoning, and contextual understanding for AI-driven applications. This is a chance to architect and own end-to-end Knowledge Graph projects that shape the backbone of enterprise AI systems.


In this role, you will:

  • Design, develop, and maintain large-scale Knowledge Graphs, from ontology and schema design to entity extraction and linkage.
  • Integrate Knowledge Graphs with LLMs to enable contextual reasoning, enrichment, and retrieval augmentation.
  • Lead cross-functional initiatives, guiding teams through the full lifecycle from concept to deployment.
  • Build and operate production-grade services using Python, REST APIs, and microservices within modern cloud environments (AWS, Kubernetes).
  • Work hands-on with graph databases such as Neo4j or Neptune to deliver optimized, high-performance solutions.
You’ll bring:
  • Proven expertise in Knowledge Graph development and integration with AI/LLM systems.
  • Strong software engineering background, Python preferred, with exposure to Java, Scala, or Go.
  • Solid understanding of cloud-native architecture, distributed systems, and data pipelines.
  • A builder’s mindset and the ability to lead technically while staying close to the code.
Bonus points for:
  • Experience with retrieval systems or vector databases (Pinecone, Weaviate).
  • ML/LLM experience in semantic search, code generation, or reasoning.
  • Big-data experience with Spark or similar frameworks.
  • Contributions to open-source ML or AI projects.
Why join?
This is a unique opportunity to make an impact at scale, helping design the data and intelligence layer behind next-generation enterprise AI systems. Expect world-class benefits, flexible hybrid working, a culture of ownership, and the chance to leave your mark on an innovative platform shaping the future of data-driven AI.


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