About the job
Join Us in Building a Safer World.
At TRM Labs, we harness the power of blockchain analytics and AI technologies to empower law enforcement, national security agencies, financial institutions, and cryptocurrency enterprises in the fight against crypto-related fraud and financial crime. Our advanced platforms provide critical insights to trace fund origins, identify suspicious activities, and construct comprehensive threat landscapes. Trusted by leading organizations globally, TRM is committed to fostering a safer, more secure world for everyone.
We invite you to become a part of our Knowledge Layer team, dedicated to extracting, structuring, and analyzing vast amounts of unstructured data. This pivotal team focuses on knowledge graphs, entity resolution, graph extraction, and graph analytics, supporting the development of TRM’s core intelligence offerings.
We seek a passionate Senior Full Stack Data Scientist to amplify our machine learning and data science capabilities. You will bring practical ML expertise—particularly in knowledge extraction and graph-based ML—to the table, enabling us to innovate and scale our solutions effectively. This role is perfect for someone who thrives in end-to-end operations, from model selection and experimentation to rolling out ML systems and APIs.
Your Impact:
Design, develop, and implement machine learning models aimed at:
Knowledge extraction from unstructured data (e.g., Named Entity Recognition, entity linking)
Graph-based learning and inference
Entity resolution and relationship discovery
Analyze existing ML models and frameworks to address real-world challenges efficiently
Collaborate closely with backend and graph engineers to integrate ML models into production services and APIs
Contribute to the design and enhancement of knowledge graphs and ontologies
Conduct exploratory data analysis (EDA) to guide modeling decisions and system architecture
Manage ML components end-to-end, including experimentation, evaluation, deployment, and iterative improvement
Help establish best practices for applied ML within the Knowledge Layer team
Desired Qualifications:
Proven experience in machine learning and data science, particularly with knowledge extraction and graph-based methods
Strong programming skills in languages such as Python or R
Familiarity with ML frameworks and libraries (e.g., TensorFlow, PyTorch)
Effective communication skills to collaborate with technical and non-technical stakeholders

