Machine Learning Systems Engineer

Position: Machine Learning Systems Engineer (1 Year Fixed Term)
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The Department of Ophthalmology in the School of Medicine at Stanford University is launching an interdisciplinary Neuro-AI project dedicated to building a foundation model of the brain. This endeavor will involve multiple labs and faculty across the Stanford campus, including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute. Leveraging cutting-edge advances in electrophysiology and machine learning, this project aims to create a functional "digital twin" — a model that captures both the activity dynamics of the brain at cellular resolution and the intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving.

This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking talented systems engineers with extensive experience in large scale data and compute clusters. As a Systems Engineer, you will be responsible for designing, deploying, and maintaining the compute infrastructure that supports our machine learning and data pipeline operations.

This position promises a vibrant and cooperative atmosphere within the laboratories of Andreas Tolias ((Use the "Apply for this Job" box below).), Tirin Moore () and other labs at Stanford University renowned for their expertise in perception, cognition, pioneering neural recording techniques, computational neuroscience, machine learning, and Neuro-AI research.

Duties Include

• Design and develop complex and specialized equipment, instruments, or systems; coordinate detailed phases of work related to responsibility for part of a major project or for an entire project of moderate scope.

• Develop technical and methodological solutions to complex engineering/scientific problems requiring independent analytical thinking and advanced knowledge.

• Develop creative new or improved equipment, materials, technologies, processes, methods, or software important to the advancement of the field.

• Contribute technical expertise, and perform basic research and development in support of programs/projects; act as advisor/consultant in area of specialty.

• Contribute to portions of published articles or presentations; prepare and write reports; draft and prepare scientific papers.

• Provide technical direction to other research staff, engineering associates, technicians, and/or students, as needed.
• * - Other duties may also be assigned

What We Offer

• Work on a collaborative and uniquely positioned project spanning several disciplines, from neuroscience to artificial intelligence and engineering.

• Work jointly with a vibrant team of researchers and scientists in a project dedicated to one mission, rooted in academia but inspired by science in industry.

• Competitive salary and benefits.

• Strong mentoring in career development.
Application

In addition to completing the application, please send your CV and one page interest statement to:

Desired Qualifications

• 3+ years of experience in designing, managing and running large-scale compute infrastructure in the context of machine learning

• Experience with containerization technologies like Docker and orchestration platforms like Kubernetes or SLURM

• Proficiency in scripting languages such as Python, Bash, or Power Shell

• Strong knowledge of Linux/Unix systems administration

• Ability to work effectively in a collaborative, multidisciplinary environment

• Familiarity with modern distributed big data tools and pipelines such as Apache Spark, Arrow, Airflow, Delta Lake, or similar

• Familiarity with machine learning frameworks like PyTorch or JAX

• In-depth experience with cloud computing…