Software Developer, Machine Learning​/ ML Engineer, Software Engineer

Software Developer 1 (1 Year Fixed Term) at Stanford University summary:

This Software Developer role at Stanford University's Department of Ophthalmology supports an interdisciplinary Neuro-AI project focused on building a brain foundation model integrating neuroscience and artificial intelligence. The position involves developing and maintaining production-grade software, implementing CI/CD pipelines, and collaborating closely with scientists and engineers to ensure high-quality, reproducible code. The role requires expertise in programming, software engineering best practices, and experience with containerization and machine learning frameworks within a fast-paced research environment.

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 software developers/engineers to support the whole team by developing and scaling the systems that allow our scientists to iterate quickly. In this role, you will play a critical role in ensuring the reproducibility and production-readiness of our codebase, as well as implementing Continuous Integration and Continuous Deployment (CI/CD) processes for all teams involved in the project.

Your work will be essential in maintaining the highest standards of software quality, reliability, and efficiency.

This position promises a vibrant and cooperative atmosphere within the laboratories of Andreas Tolias ( ), 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.

Role & Responsibilities:

• Develop and maintain reproducible, production-grade software/library for various aspects of the project, including data processing, machine learning, and data/compute infrastructure management

• Implement and manage CI/CD pipelines using tools like Git Hub Actions, Code Coverage, and unit testing frameworks

• Collaborate with data scientists, machine learning engineers, and systems engineers to ensure seamless and timely integration of code and infrastructure

• Help establish and enforce coding standards, best practices, and documentation guidelines across the project

• Conduct code reviews and provide constructive feedback to maintain code quality and consistency

• Optimize code performance, scalability, and reliability

• Troubleshoot and debug software issues, and provide timely solutions

• Stay up-to-date with the latest trends and best practices in software engineering and CI/CD methodologies

Duties include:

• Assess user needs and requirements.
• Design and develop applications that may involve sophisticated data manipulation.
• Maintain and update existing programs.
• Troubleshoot and solve technical problems.
• Create programs to meet reporting and analysis needs.
• Design and implement user and operations training programs.
• Document changes in software for end users.
• Follow team software development methodology.
• Serve as technical resource with respect to applications.
• * - 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…