About the job
At GRAIL, our mission is to revolutionize cancer detection by identifying it at an early stage when treatment can be most effective. We strive to alter the landscape of cancer mortality by uniting various stakeholders in the adoption of groundbreaking, safe, and efficient technologies that can truly transform cancer care.
As a pioneering healthcare company, GRAIL is at the forefront of advancing early cancer detection technology. Our multi-disciplinary team, consisting of scientists, engineers, and physicians, utilizes cutting-edge next-generation sequencing (NGS), large-scale clinical studies, and advanced data science techniques to tackle one of the greatest challenges in medicine.
Headquartered in the Bay Area, GRAIL also has locations in Washington, D. C., North Carolina, and the United Kingdom. We are backed by prominent global investors and partners from the pharmaceutical, technology, and healthcare sectors.
We are currently looking for a Staff Machine Learning Infrastructure Engineer to join our Research Platform Engineering team. This software engineering role involves developing and maintaining systems that support machine learning and analysis workflows with controlled data. You will empower computational biologists, data scientists, and statisticians in crafting and refining powerful diagnostic products by facilitating efficient exploratory research and classifier development.
The ideal candidate is someone who has a strong passion for reliable software infrastructure, distributed computing, reproducible research, and adept problem-solving skills. Given the collaborative nature of this role, excellent communication skills and experience working with diverse, multidisciplinary teams are essential.
This position is hybrid, based in Menlo Park, CA, with plans to relocate to Sunnyvale, CA in Fall 2026. Our current hybrid policy requires a minimum on-site presence of 40%, particularly on key collaboration days, which are Tuesdays and Thursdays at our Menlo Park campus.
