The Engineering group within Prescient Design seeks exceptional machine learning engineers who have a demonstrated background in machine learning, a passion for technical problem-solving, and a proven ability to implement ideas from research into production.
The group provides a dynamic and challenging environment for cutting-edge, multidisciplinary research including access to heterogeneous data sources, close links to top academic institutions around the world, as well as internal Genentech Research and Early Development (gRED) partners and research units. Our mission is to develop and apply methods in designing novel macromolecules. Engineers will primarily focus on the deep learning subfield of machine learning but should be broadly interested in implementing methods capable of effective representation learning that can help drive and sharpen the research questions we study. Fundamentally, our research goals allow us to collaborate closely with and–contribute uniquely to–many different project teams across the company.
Participate in cutting-edge research in machine learning and applications to drug discovery, design, and development.
You will collaborate closely with cross-functional teams across both Prescient Design and gRED to solve complex problems in the life sciences.
You will be expected to help manage and scale different data pipelines for training and inference.
You will be expected to solve core engineering challenges including the design, implementation, and scaling of our machine learning framework and algorithms.
B.S., M.S., or Ph.D. in Computer Science, Statistics, Applied Mathematics, Computational Biology, Physics, related technical field, or equivalent practical experience.
At least one year relevant work experience.
Strong programming skills in languages like C++, Python, Java, Scala, Rust, or Go.
Experience with one or more of the following: PyTorch/PyTorch Lightning, TensorFlow, JAX.
Experience with cloud computing and infrastructure including Amazon Web Services (AWS) and distributed computing libraries like Apache Spark.
Experience with containzeration and orchestration tools like Docker, Singularity, and Kubernetes.
Experience with deploying and maintaining deep learning systems and services in production at scale, including using MLOps frameworks like Weights & Biases.
Experience developing and maintaining codebases and software libraries, following industry best practices.
Intense curiosity about the biology of disease and eagerness to contribute to scientific and computational efforts.
Who We Are
Genentech, a member of the Roche group and founder of the biotechnology industry, is dedicated to pursuing groundbreaking science to discover and develop medicines for people with serious and life-threatening diseases. To solve the world's most complex health challenges, we ask bigger questions that challenge our industry and the boundaries of science to transform society. Our transformational discoveries include the first targeted antibody for cancer and the first medicine for primary progressive multiple sclerosis.
Diversity and Inclusion (D&I) are critical to the success of our company and our impact on society. We believe that by championing diversity of background, thought and experience, we can foster a sense of belonging and provide an environment where every employee feels valued, included, and able to contribute their best for the patients we serve. We’re focused on attracting, retaining, developing and advancing our people to their full potential by rewarding bold ways of thinking and integrating inclusive behaviors into every aspect of our work.
Genentech is an equal opportunity employer & prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, disability, marital & veteran status. For more information about equal employment opportunity, visit our Genentech Careers page.