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.
At Genentech Computational Sciences (gCS) Prescient Design, we are seeking a highly motivated Machine Learning Scientist to help drive research on Machine Learning for Drug Discovery. The successful candidate will collaborate extensively with computational and experimental scientists and researchers across gRED to deploy and deliver machine-learning solutions for small-molecule drug discovery.
The Opportunity
We are seeking a highly motivated Machine Learning Scientist to join Prescient Design within Genentech Research and Early Development (gRED) to help drive research on Machine Learning for Drug Discovery, with a focus on Large Language Models (LLMs) and Chemistry/Small Molecule Drug Discovery (SMDD). The successful candidate will focus on creating novel LLM applications that interface directly with medicinal chemistry and molecular design processes, as well as enhancing predictions of biochemical properties, chemical reactivity, and synthesizability. By collaborating extensively with computational and experimental scientists across gRED, the candidate will develop, deploy, and deliver innovative machine-learning solutions that significantly advance our small-molecule drug discovery pipeline.
Who you are
Preferred
#gCS
#tech4lifeAI
Relocation benefits are available for this posting
The expected salary range for this position based on the primary location of California or New York is $165,200 – 306,800. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors.
Benefits
Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.
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