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, and is seeking a Systems Engineer to design, deploy, and maintain the compute infrastructure that supports machine learning and data pipeline operations.
Requirements
- 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 PowerShell
- Strong knowledge of Linux/Unix systems administration
- 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 resources
Responsibilities
- 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.
- Design, deploy, and maintain the compute infrastructure that supports machine learning and data pipeline operations.
Other
- Bachelor's degree and three years of relevant experience, or combination of education and relevant experience.
- Thorough knowledge of the principles of engineering and related natural sciences.
- Demonstrated project management experience.
- Ability to work effectively in a collaborative, multidisciplinary environment
- Travel may be required
