Machine Learning Systems Developer

We are excited to announce the launch of an interdisciplinary Neuro-AI initiative within the Department of Ophthalmology at Stanford University's School of Medicine. This project focuses on creating a foundation model of the brain, collaborating with various labs and faculty members across the Stanford campus, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. Our effort will harness the latest advancements in electrophysiology and machine learning to develop a functional "digital twin" of the brain, accurately capturing its dynamic activity at the cellular level and the intelligent behaviors it produces, such as perception, motor planning, learning, reasoning, and problem-solving. As a Systems Engineer, you will play a pivotal role in supporting our machine learning and data pipeline operations by designing, deploying, and maintaining our computing infrastructure. You will be part of a vibrant team of researchers and scientists, working on a project that spans several disciplines from neuroscience to artificial intelligence and engineering. We offer a competitive salary and benefits, as well as strong mentoring for your professional development. Join us on this ambitious journey toward understanding the algorithms of perception and cognition, while also aligning artificial intelligence models with human-like neural representations in a collaborative environment.