Member of the Technical Staff, Cheminformatics

About the role

This role will focus on developing computational approaches that combine chemistry, machine learning, and software engineering to evaluate molecular structures and synthetic feasibility. The successful candidate will partner closely with drug discovery and model teams to improve how chemical information is interpreted and applied. This is an opportunity to help build scalable tools and pipelines that support informed molecular assessment in a highly collaborative, innovation-driven environment.

Responsibilities

• Develop and train models incorporating chemical synthesis knowledge
• Build scalable computational tools to evaluate synthetic feasibility of molecular libraries
• Interpret chemical terms from model inputs and outputs for clarity
• Collaborate with drug discovery and model teams for molecular evaluation
• Maintain cheminformatics pipelines for molecular analysis and assessment

Qualifications

• PhD in chemistry, computational chemistry, cheminformatics, or a related field with 2+ years of post-doctoral or industry research experience, or a Master's degree with 5+ years of experience
• Deep understanding of organic chemistry and synthetic routes
• Experience training machine learning models on molecular and chemical data
• Strong programming skills in Python with experience in computational pipelines
• Understanding of drug-like properties and medicinal chemistry principles

Benefits

• Encouragement of new ideas and creative thinking
• Feedback-focused environment with strong support for professional growth
• Autonomy in managing day-to-day responsibilities
• Excellent medical, dental, and vision coverage