Full Stack - Principal Software Engineer, Drug Discovery

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
** You will collaborate closely with Prescient's AI scientists and engineers, Genentech Computational Sciences (gCS) colleagues, including machine learning specialists, Genentech Research & Early Development (gRED) Drug Discovery teams like Antibody Engineering, and other teams across the Roche group.

Your role will be key in identifying, strategizing, and productionalizing high-impact AI applications across the drug discovery pipeline. Prescient Design offers a dynamic environment for cutting-edge, multidisciplinary research in AI and drug discovery, providing access to rich data sources, close links to top academic institutions, and internal Genentech and Roche partners.
** In this role, you will:
*** Contribute to the strategic roadmap for the Prescient "Lab-in-the-Loop" platform, guiding product features and technical architecture to maximize AI impact in drug discovery.
* Take a leading role in the full-stack design and development of scalable, reliable software systems, including crafting responsive and intuitive front-end applications that form the core of our AI/ML platform.
* Collaborate closely with Machine Learning Scientists, AI Engineers, and experimental specialists, translating complex scientific workflows into intuitive user interfaces, dashboards, and analytics tools with a strong focus on user experience.
* Explore and implement integrations with novel AI agents and models to enhance platform capabilities and automate complex tasks.
* Mentor and provide technical guidance to other software engineers on the team, fostering best practices and high-quality engineering.
** Who you are
*** 10 + years of software engineering work experience, delivering complex, full-stack applications.
* Proven expertise in front-end development using modern frameworks (e.g., React, Angular) and building intuitive, user-centered interfaces.
* Intense curiosity about the biology of disease and eagerness to contribute to scientific and computational efforts.
* Proficiency with Python and SQL
** Preferred
* ** Familiarity with ML concepts or frameworks (e.g., PyTorch).
* Domain experience in drug discovery, computational biology, bioinformatics and cheminformatics

Relocation benefits are available for this job posting

The expected salary range for this position, based on the primary location of New York is $155,.  Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.  A discretionary annual bonus may be available based on individual and Company performance.  This position also qualifies for the benefits detailed at the link provided below.#Computation

CoE#tech4life

Computational Science Genentech  is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

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