|
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. The Opportunity At Roche's AI for Drug Discovery (AIDD) group (Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning techniques. Prescient Design is developing cutting-edge machine learning for drug discovery, building new methods, techniques, and systems to fundamentally transform how drugs are designed. We are seeking a highly motivated Machine Learning Scientist to help drive research on Machine Learning for Drug Discovery, with a focus on Small Molecule Drug Discovery (SMDD). The successful candidate will develop, deploy, and deliver innovative ML solutions that accelerate molecular design, prediction, and hypothesis generation, working closely with computational and experimental collaborators across gRED and Roche. In this role, you will:
Design, build, and apply machine learning methods to key challenges in small molecule drug discovery, including molecular property prediction, protein-ligand modeling, chemical reactivity, and synthesizability. Develop robust and scalable ML pipelines that integrate with cheminformatics, structural biology, and computational chemistry tools. Collaborate with computational chemists, medicinal chemists, structural biologists, and experimental scientists to generate testable hypotheses and guide design decisions. Curate, integrate, and leverage diverse biochemical, biophysical, and chemical datasets to power ML models and workflows. Explore and apply a range of ML approaches - from deep learning (transformers, graph neural networks) to physics-informed and hybrid methods - for impactful applications in drug discovery. Deploy models and workflows into production research environments, ensuring reproducibility and scalability. Contribute to and drive publications, present results at internal and external scientific conferences, and help make code and workflows open source.
Who you are
You have a PhD in the physical sciences (e.g., Chemistry, Physics, Chemical Engineering) or quantitative fields (e.g., Computer Science, Statistics, Applied Mathematics) with 0 - 3 years experience, or equivalent industry research experience. You have a strong background in scientific software development and ML engineering, with demonstrated ability to design, train, and deploy ML models. You have experience working with biochemical, chemical, or biophysical datasets; familiarity with cheminformatics and small molecule drug discovery concepts. You are fluent in Python and experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow, Hugging Face) You have a familiarity with commonly used toolkits for chemical modeling (e.g., RDKit, OpenEye, OpenMM, Schrodinger)
Preferred
Experience with cloud platforms (AWS, GCP, or Azure), version control (Git), and CI/CD pipelines. Record of scientific excellence as evidenced by at least multiple publications in a scientific journal or conference. Public portfolio of projects available on GitHub/GitLab is a plus.
Relocation benefits are available for this job posting. The expected salary range for this position, based on the location of California, is $167,400 - 310,800. 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. Benefits #ComputationCoE #tech4lifeComputationalScience #tech4lifeAI 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. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
|
Genentech
Sep 25, 2025