About the job
Join Us in Building a Safer World.
At TRM Labs, we are dedicated to providing cutting-edge blockchain analytics and AI solutions that empower law enforcement, national security agencies, financial institutions, and cryptocurrency businesses in the fight against crypto-related fraud and financial crime. Our advanced platforms enable clients to trace the origins and destinations of funds, identify illicit activities, build robust cases, and gain a comprehensive view of potential threats. Trusted by leading agencies and businesses globally, TRM is committed to fostering a safer and more secure world for everyone.
We are currently seeking a Full Stack Data Scientist to join our dynamic Knowledge Layer team. This innovative group specializes in extracting, structuring, and analyzing knowledge from vast, unstructured datasets. Positioned at the crossroads of knowledge graphs, entity resolution, graph extraction, and graph analytics, this team plays a pivotal role in enhancing TRM’s core intelligence products.
While our team boasts strong backend and graph engineering expertise, we are in search of a candidate who can serve as the voice of machine learning and data science within the team. This individual will bring practical expertise in knowledge extraction and graph-based machine learning to help accelerate and scale our capabilities. This role is perfect for someone who thrives in an end-to-end operational environment, managing everything from model selection and experimentation to the productionization of ML systems and APIs.
Your Impact:
Design, build, and productionize machine learning models centered on:
Knowledge extraction from unstructured data (e.g., Named Entity Recognition, entity linking)
Graph-based learning and inference
Entity resolution and relationship discovery
Evaluate and utilize existing ML models and frameworks to effectively tackle real-world challenges
Collaborate closely with backend and graph engineers to integrate ML models into production services and APIs
Contribute to the design and development of knowledge graphs and ontologies
Conduct exploratory data analysis (EDA) to inform modeling decisions and system architecture
Oversee ML components from inception to deployment, including experimentation, evaluation, and iterative improvements
Help establish best practices for applied ML within the Knowledge Layer team
Qualifications:
- Proven experience in machine learning, particularly in knowledge extraction and graph-based methods
- Strong programming skills in Python or similar languages
- Familiarity with ML frameworks and libraries (e.g., TensorFlow, PyTorch)
- Experience with data manipulation and analysis tools (e.g., Pandas, NumPy)
- Excellent communication skills and ability to collaborate effectively with cross-functional teams

