Graph ML Engineer — Knowledge Layer & Production AI

TRM Labs; Oregon; Hybrid; USD 180,000 - 210,000; Full time

Benefits offered by this job

Equity plan

Job summary

TRM Labs is hiring a Full Stack Data Scientist / ML Engineer to join the Knowledge Layer team. You will lead knowledge extraction from unstructured data, build graph-based ML models, and implement entity resolution to strengthen production services and APIs.

Applicants should have 5+ years in data science or ML engineering, strong Python skills, and experience deploying models in production. A background in NLP and knowledge graphs is highly valued, with collaboration across engineering teams

Qualifications

• 5+ years of experience in data science, ML engineering, or applied ML
• Strong programming in Python
• Hands-on experience deploying ML models to production
• Familiarity with NLP or information extraction techniques (NER, text classification, embeddings)
• Experience or interest in knowledge graphs, graph data, or graph-based ML
• Solid software engineering fundamentals, including building or maintaining APIs/services
• Ability to translate ambiguous problems into practical ML solutions
• Strong communication and cross-functional collaboration skills

Responsibilities

• Design, build, and productionize ML models for knowledge extraction and graph-based learning
• Develop and deploy NLP/NER and entity resolution components
• Enhance knowledge graphs and ontologies and integrate ML into production services
• Collaborate with backend/graph engineers to deploy ML models through APIs
• Conduct exploratory data analysis to guide modeling and system design
• Own ML components end-to-end, from experimentation to iteration and monitoring

Skills

Python

Production ML

NER

Knowledge graphs

APIs

Communication

Job description

TRM Labs is hiring a Full Stack Data Scientist / ML Engineer to join the Knowledge Layer team. You will lead knowledge extraction from unstructured data, build graph-based ML models, and implement entity resolution to strengthen production services and APIs.

Applicants should have 5+ years in data science or ML engineering, strong Python skills, and experience deploying models in production. A background in NLP and knowledge graphs is highly valued, with collaboration across engineering teams