Senior Machine Learning Engineer, AI Drug Discovery; Lab Loop

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 the 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 Prescient Design, Roche's AI for Drug Discovery group, we’re building Lab‑in‑the‑Loop - Genentech’s platform that couples generative ML with automated wet‑lab experimentation to continuously design, test, and learn from new therapeutic molecules. The result is a closed feedback loop: models propose candidates, the lab runs assays, we ingest results, and the system gets smarter with every cycle. This isn’t theoretical: our Lab‑in‑the‑Loop work has already shown multi‑round optimization on clinically relevant targets (EGFR, IL‑6, HER2, OSM), testing thousands of variants with multiply 100x affinity gains and best binders in the 100pM range.

To power this ambition, we need a strong technical contributor who can turn cutting‑edge ML and wet‑lab automation into a robust product, by building intuitive UIs scientists love, and reliable services that orchestrate experiments, data, and models. This work will ship into active discovery programs with a clear line‑of‑sight to patients.

You will work closely with Roche colleagues, including our AI for drug development team, Genentech Research & Early Development (gRED) Drug Discovery teams including the Antibody Engineering division, and other teams across the Roche family of companies to identify, strategize, and productionalize high-impact applications from across the drug discovery and development pipeline. Genentech provides a dynamic and challenging environment for cutting-edge, multidisciplinary research in AI and drug discovery including access to rich sources of data, close links to top academic institutions around the world, as well as internal Genentech and Roche partners and research units.

In this role, you will:

• Shape the strategic roadmap for Lab‑in‑the‑Loop, influencing its features and technical architecture.

• Build and enhance our full-stack platform, crafting intuitive front-end applications and engineering the reliable backend services that orchestrate the entire discovery cycle.

• Partner directly with ML scientists and experimentalists, translating complex scientific workflows into elegant and effective product features.

• Build the critical integrations that close the loop with the wet lab, connecting our platform with robotics, assay pipelines, and instrumentation data.

• Engineer the systems that bring our AI to life by integrating novel generative models and building the infrastructure for their evaluation and deployment.

Who you are

• 3+ years building and operating complex, full‑stack applications (you’ve owned systems in production).

• Proven front‑end expertise with modern frameworks (e.g., React, Angular) and a track record of delivering intuitive, user‑centered interfaces.

• Proficiency with Python and SQL; comfortable designing data models and pipelines.

• Strong system design skills: domain modeling, event‑driven architecture, concurrency/failure modes, performance profiling.

• Familiarity with machine learning concepts, model training, serving, and evaluation.

• Practical hands-on experience with PyTorch in a production environment.

Preferred

• Curiosity about the biology of disease and eagerness to contribute to scientific and…