Lead Data Engineer - AI/ML

1 day ago

Palo Alto, CA, USAStaff+

Responsibilities

Build end-to-end data pipelines and infrastructure for machine learning models used by data science teams.
Design and support data-processing software, compute frameworks, analysis tooling, and model implementations.
Define technical designs and interface decisions for data processing and analysis pipelines.
Train, develop, and validate researcher-built or vendor-provided machine learning algorithms using hospital data.
Troubleshoot and debug infrastructure and environment issues across production and non-production systems.
Coordinate with Stanford Health Care technology groups on server maintenance, system requirements, data usage, and security requirements.
Oversee, develop, or implement machine learning operations processes.
Mentor junior engineers and enforce code-quality best practices.

At least 5 years of experience building data infrastructure for analytics teams.
Proficiency writing SQL, R, or Python to process large datasets in distributed cloud environments.
Bachelor’s or master’s degree in computer science, engineering, or a related field, or equivalent working experience.
Experience with cloud deployment strategies and CI/CD.
Experience building and working with data infrastructure in a SaaS environment.
Knowledge of multiple programming languages and the ability to select languages based on project requirements.
Knowledge of resource management and automation approaches such as workflow runners.
Collaborative approach and willingness to learn new programming languages as needed.