Software Development Engineer, AI for Drug...

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

The Opportunity

At Genentech and Roche, we are at the forefront of a revolutionary transformation in drug discovery. We are seeking an exceptional Software Engineer to join the team building our next-generation Therapeutic Molecule Registration (TMR) platform. This platform serves as the central nervous system for managing and integrating molecular data across our global research organization. As we scale our Lab-in-the-Loop ( https://www.youtube.com/watch?v=cN1PxxQWoEc ) strategy, you will build high-performance, cloud-native systems capable of supporting the rapid iteration cycles between computational design and experimental validation. While this role involves data-heavy systems, it is fundamentally a Software Engineering position focused on building robust, scalable applications and services that unlock the full potential of AI-generated molecular designs.

In this role, you will:

• Develop & Scale: Architect and implement core features of our TMR platform using clean, well-tested code.

• Systems Integration: Build and maintain high-efficiency data pipelines to ensure seamless flow between experimental labs and AI models.

• Cloud Architecture: Design and deploy production-grade services within a cloud-native environment (AWS).

• Data Evolution: Facilitate complex data migrations and contribute to the harmonization of global molecule registration systems.

• Collaborate: Participate in deep technical discussions, code reviews, and cross-functional planning with ML and Antibody Engineering teams.

• Experience: 3+ years of professional Software Engineering experience with a solid grasp of Computer Science fundamentals.Technical Stack: Proficiency in Python and strong experience with PostgreSQL.

• Cloud Infrastructure: Practical experience with cloud computing platforms (preferably AWS).

• Engineering Rigor: Proven track record of building and maintaining data pipelines and applying rigorous testing practices.

• Education: Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.

Preferred

• Domain Expertise: Educational background or professional experience in Biology, Biochemistry, or Chemistry.

• Scientific Software: Previous experience building tools for scientific research or laboratory environments.

• Full-Stack Capability: Experience with both frontend and backend implementation and modern schema design.