Senior Data & AI Engineer - Healthcare BI & ML

Stanford Health Care; California; On-site; USD 151,000 - 200,000; Full time

Job summary

Stanford Health Care's Stanford Blood Center is seeking a Sr Data & AI Solutions Engineer to design AI models, integrate ML into operations, and lead end-to-end ETL pipelines that unify data across databases and the EDW to improve outcomes and optimize resources.

The role emphasizes Python-based analytics, LLM/LLMs, BI tooling, and collaboration with clinical and operational teams, with strong focus on data governance, security, and scalable data architectures in Palo Alto, CA.

Qualifications

• Bachelor's Degree in engineering, computer science, data science or related field plus 4 years of experience with applied problems required
• Master's Degree in engineering, computer science, data science or related field preferred
• 3+ years to 5 years hands-on experience designing and developing software (across the full lifecycle), AI, and BI solutions.

Responsibilities

• Applies solid software development and object-oriented programming to build applications and front-end web solutions.
• Builds, deploys, and maintains AI and ML solutions across clinical, laboratory, and operational domains.
• Utilizes Python data science capabilities and REST APIs to accelerate analytics delivery and build scalable data pipelines.
• Leverages LLMs/SLMs to fine-tune and deploy AI solutions that enhance business analytics.
• Develops BI/ETL processes and manages a common data model to harmonize relational databases and optimize the EDW.

Skills

Python

OOP

AI/ML deployment

BI tools

SQL

EDW

Power BI

Tableau

Django

Java

Education

Bachelor's degree

Master's degree

Tools

REST APIs

SQL Server

Oracle

Azure DevOps Server

SSIS

Job description

Stanford Health Care's Stanford Blood Center is seeking a Sr Data & AI Solutions Engineer to design AI models, integrate ML into operations, and lead end-to-end ETL pipelines that unify data across databases and the EDW to improve outcomes and optimize resources.

The role emphasizes Python-based analytics, LLM/LLMs, BI tooling, and collaboration with clinical and operational teams, with strong focus on data governance, security, and scalable data architectures in Palo Alto, CA.