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.

This is an ideal role for someone who enjoys operating end-to-end: from model selection and experimentation, to productionizing ML systems and APIs.

The impact you will have

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

What we’re looking for

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

The following represents the expected range of compensation for this role

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.

Application Instructions

If you’re interested in joining TRM, we encourage you to apply directly. Every application is reviewed by our Talent team.

Before applying, review the job description carefully and highlight the experience and impact that best demonstrate the required qualifications. Please also provide thoughtful and accurate answers to the application questions, as these will be used to evaluate your skills and qualifications for the role.