Senior Machine Learning Engineer, Knowledge Layer

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

Overview

Build a Safer World. TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM's platforms enable investigators to trace illicit activity, build cases, and construct operating pictures of threat networks. Leading agencies and businesses worldwide rely on TRM to make the world safer and more secure.

We’re looking for a Full Stack Data Scientist / Machine Learning Engineer to join our Knowledge Layer team, a group focused on extracting, structuring, and analyzing knowledge from large-scale, unstructured data. This team sits at the intersection of knowledge graphs, entity resolution, graph extraction, and graph analytics, and plays a critical role in powering TRM’s core intelligence products. While the team has strong backend and graph engineering expertise, we are looking for someone to be the machine learning and data science voice in the room — bringing practical ML expertise, especially in knowledge extraction and graph-based ML, to help accelerate and scale our capabilities.

Impact

• Design, build, and productionize machine learning models focused on:
• Knowledge extraction from unstructured data (e.g., NER, entity linking)
• Graph-based learning and inference
• Entity resolution and relationship discovery
• Evaluate and leverage existing ML models and frameworks to solve real-world problems efficiently
• Partner closely with backend and graph engineers to integrate ML models into production services and APIs
• Contribute to the design and evolution of knowledge graphs and ontologies
• Perform exploratory data analysis (EDA) to inform modeling decisions and system design
• Own ML components end-to-end, including experimentation, evaluation, deployment, and iteration
• Help shape best practices for applied ML within the Knowledge Layer team

Qualifications

• 5+ years of experience in data science, machine learning engineering, or applied ML
• Strong programming experience in Python
• Hands‑on experience building, training, or deploying machine learning models in production
• Familiarity with NLP or information extraction techniques, such as Named Entity Recognition (NER), text classification, or embedding-based approaches
• Experience or strong interest in knowledge graphs, graph data, or graph-based ML
• Solid software engineering fundamentals, including building and maintaining APIs or services
• Ability to translate ambiguous problem spaces into practical ML solutions
• Strong communication skills and comfort collaborating with engineers across disciplines

Compensation

Individual pay is determined by skills, qualifications, experience, and location. The compensation details listed in this posting reflect the US base salary only.

The estimated base salary range for this role is $180,000 - $210,000.

Additionally, this role may be eligible to participate in TRM’s equity plan.

Please note – we factor in the different costs for geographies outside the United States.

Work Week Travel

This role requires participation in in-person R&D work weeks, typically 1-2 times per quarter, at a TRM hub or other designated location. Work weeks may be scheduled with as little as 14 days’ notice, and some roles may require additional travel based on team and cross-functional needs. TRM coordinates and covers approved travel, lodging, and workspace. Accommodations are available for legitimate caregiving, health, immigration, and similar constraints.

Interview Process

Interviewing with TRM

The process is designed to understand how you think, solve problems, and deliver impact, while allowing you to evaluate TRM. Most interview processes include a case study, an AI skills assessment, and a Leadership Principles interview.

Recruiter Intro

Qualifications, motivations, and alignment with the role.

Hiring Manager

Deep dive into your relevant experience, skills, and impact.

First Round

1-2 interviews focused on the skills most critical to the role.

Final Round

Hands‑on