Senior Software Engineer - Drug Discovery

2w2 weeks ago

Genentech

South San Francisco, US · Full-time · $142,500 – $264,700

About this role

Advances in AI, data and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organizations at Genentech (gRED) and Pharma (pRED) leverage these technologies to accelerate R&D. The Computational Sciences Center of Excellence (CS CoE) harnesses data and AI to deliver innovative medicines for patients worldwide.

The Data and Digital Catalyst - Solutions group within the CS CoE modernizes computational and data ecosystems. It integrates digital technologies across Research and Early Development to empower stakeholders and advance data-driven science. The team builds Data Pipelines and Applications for data acquisition, collection, storage, transformation, linkage and sharing.

Design and develop scientific software platforms that enable the capture, analysis, storage, and reporting of research data related to therapeutic molecules. Work closely with Data Engineers, Product Leaders, Tech/ML Ops, Computational Scientists, ML Scientists, and Research Scientists. Build robust and scalable systems that unlock diverse scientific data potential.

Work directly with cross-functional teams to deliver intuitive, sustainable software solutions addressing urgent scientific challenges. Own and drive software initiatives through design, implementation, testing, and deployment. Accelerate the discovery and development of life-changing treatments for patients.

Requirements

Background in drug discovery, protein science, or related scientific field
Bachelor’s or Master’s degree in Computer Science or similar technical field, or Ph.D. in Protein Science or a closely related field, plus 6+ years of professional experience in full-stack software development
Strong proficiency in Python or Java, plus experience with a frontend or backend web framework
Experience with databases, data transformations, and data access
Experience working on cloud-native architectures in public clouds (ideally AWS)
Proven understanding and application of engineering best practices and ability to quickly adapt to new technologies
An AI-first approach to development, user experience, and data access

Responsibilities

Work directly with cross-functional teams across the drug discovery research organization to deliver intuitive, sustainable software solutions addressing urgent scientific challenges
Design and implement robust, scalable, and maintainable software platforms for collecting, structuring, and storing diverse scientific data that support advanced analytics, machine learning, and other data-driven initiatives
Understand, maintain, and evolve existing critical applications into extensible platforms
Own and drive software initiatives through design, implementation, testing, and deployment
Develop platforms enabling capture, analysis, storage, and reporting of research data related to therapeutic molecules
Build data pipelines for protein sciences and drug discovery data integration