Senior Machine Learning Engineer, AI for Drug Discovery (Lab in the Loop) at Genentech
New York, NY 10001, USA -
Full Time


Start Date

Immediate

Expiry Date

06 Dec, 25

Salary

297300.0

Posted On

07 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

THE POSITION

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.

Responsibilities
  • 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.
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