Principal Machine Learning Engineer

What you'll do

• Design graph inference pipelines, schemas, permissions, and evaluation frameworks for inferred work context.
• Integrate graph context into Rovo Chat and build low-latency APIs and CLI experiences for real-time access.
• Set technical direction across teams, mentor engineers, and promote responsible, privacy-safe AI and data quality.

What they ask for

• 8+ years in ML/AI engineering, with deep expertise in knowledge graphs, graph neural networks, or entity/relationship extraction.
• Production-scale track record building and shipping ML-powered graph inference or knowledge representation systems.
• Hands-on experience with graph databases, graph query languages, or large-scale graph processing frameworks.
• Experience shipping end-to-end ML features and understanding LLM orchestration, RAG, context injection, and ML evaluation.

Nice to have

• Experience with enterprise knowledge graphs, semantic embeddings, or ontology design at scale.
• Familiarity with permission-aware systems and privacy-by-design; background in collaboration analytics, social network analysis, or user activity modeling.

Pay

$236,700 - $309,025 USD base salary; $213,030 - $278,123 USD base salary; $196,461 - $256,491 USD base salary

Tools

Neo4j, Neptune, Cypher, SPARQL, GraphX, DGL, PyG, Rovo Chat

AI focus

Builds knowledge-graph inference and personal work-context systems; uses graph-derived context to improve LLM grounding and relevance in Rovo Chat and enable real-time agent queries.