Senior Data Scientist: Graph ML & Knowledge Extraction

TRM Labs; San Francisco (CA); Presencial; USD 180.000 - 210.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity plan

Descripción de la vacante

TRM Labs is seeking a Full Stack Data Scientist / Machine Learning Engineer to join the Knowledge Layer team in San Francisco. You will own end-to-end ML components, focusing on knowledge extraction from unstructured data, graph-based learning, and entity resolution, and will collaborate across engineers to deploy models and APIs.

You should bring 5+ years in ML or data science, strong Python, and experience deploying ML models in production.

Formación

• 5+ years of experience in data science, ML engineering, or applied ML.
• Hands-on experience building, training, or deploying ML models in production.
• Familiarity with NLP or information extraction techniques (NER, text classification).
• Experience or strong interest in knowledge graphs, graph data, or graph-based ML.
• Strong Python programming and API development fundamentals.

Responsabilidades

• Design, build, and productionize ML models focused on knowledge extraction, graph-based learning, and entity resolution.
• Evaluate and leverage existing ML models to solve real-world problems efficiently.
• Partner 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.
• Own ML components end-to-end from experimentation to deployment.

Conocimientos

Python

NLP

Knowledge graphs

Graph ML

APIs

Herramientas

TensorFlow

PyTorch

SpaCy

Neo4j

Descripción del empleo

TRM Labs is seeking a Full Stack Data Scientist / Machine Learning Engineer to join the Knowledge Layer team in San Francisco. You will own end-to-end ML components, focusing on knowledge extraction from unstructured data, graph-based learning, and entity resolution, and will collaborate across engineers to deploy models and APIs.

You should bring 5+ years in ML or data science, strong Python, and experience deploying ML models in production.