TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all.
We’re looking for a Full Stack Data Scientist 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
Work Location Requirement: This role is based in our San Francisco office. Employees in this position are expected to work from the office at least three (3) days per week to support in-person collaboration and team engagement.
We are building a safer world. That promise shows up in how we work every day.
TRM runs fast. Really fast. We’re a high‑velocity, high‑ownership team that expects clarity, follow‑through, and impact. People who thrive here are energized by hard problems, experimentation, and direct feedback. If something takes months elsewhere, it often ships here in days.
That pace isn’t for everyone. If you are optimizing primarily for consistent work-life balance, use the interview process to pressure-test fit. We want teammates who thrive here, not just survive here.
AI fluency is a baseline expectation at TRM.
We believe AI meaningfully changes how top performers operate. We expect every team member to use AI to accelerate and reimagine their craft, not just automate surface tasks.
At TRM, AI fluency means you are among the top 10 percent of operators in your function in how you apply AI to:
Accelerate repeatable workflows
Structure and solve problems
Improve output quality
Increase speed and leverage
You will be evaluated on applied AI fluency during the interview process.
We hire and grow against three leadership principles. They’re the standards for how we operate, treat each other, and make decisions.
Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly.
Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end‑to‑end, and invest in getting better everyday.
Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one‑team mindset — giving and receiving feedback to make the team stronger.
This work has real stakes. Depending on your role at TRM, your week might look like:
Driving critical investigations that can’t wait for typical business hours.
Shipping products in days when others would schedule quarters.
Partnering with teams across time zones to deliver insights while the story is still unfolding.
Building new solutions from first principles when the playbook doesn’t yet exist.
Protecting victims and customers by tracing illicit activity and disrupting criminal networks.
At TRM we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you’re excited by TRM’s mission but don’t check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast.
TRM is a Series C company with $220M in total funding, backed by Blockchain Capital, Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore.
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