Lead Machine Learning Engineer Graph ML

BenchSci is seeking a Lead Machine Learning Engineer to join their Knowledge Enrichment team, focusing on advancing biomedical research through sophisticated ML applications. This role combines cutting-edge machine learning with biological data analysis, working with complex knowledge graphs and heterogeneous data sources. The position offers an opportunity to lead technical initiatives in applying state-of-the-art ML and graph ML algorithms to biomedical data.

The role involves analyzing and enriching a large biological knowledge graph, developing sophisticated ML solutions for data classification and relationship discovery, and implementing production-ready models. You'll work with various data types, from unstructured text to complex knowledge graphs, and apply advanced techniques including Large Language Models and Retrieval Augmented Generation.

As a technical leader, you'll guide a team of 5-10 engineers, collaborate with cross-functional teams, and shape ML best practices. The ideal candidate brings 8+ years of ML engineering experience, deep expertise in graph machine learning, and a strong background in implementing complex ML systems. This position offers the unique opportunity to impact healthcare and biomedical research while working with cutting-edge AI technologies.

The role is fully remote, allowing for flexible work arrangements while contributing to meaningful scientific advancement. You'll be part of a team that values innovation, embraces failure as a learning opportunity, and focuses on delivering high-impact solutions in the biomedical field.