Healthcare ML Engineer: Data Pipelines & AI Systems

Stanford University; Palo Alto (CA); Hybrid; USD 123,000 - 145,000; Full time

Benefits offered by this job

Health benefits

Tuition assistance

Flexible work options

403(b) plan

Job summary

Stanford University in Palo Alto, CA, is seeking a Machine Learning Engineer to develop end-to-end data pipelines and modular software for ML models used in healthcare research. You will work with scientists and engineers to evaluate model performance, safety, and transparency, while guiding tool and platform choices for data projects.

The role emphasizes independent work on complex data challenges within a hybrid environment and collaboration across multidisciplinary teams.

Qualifications

• Bachelor’s degree in engineering, science, or related field with relevant experience.
• Experience with Python and BigQuery SQL for large datasets.
• Familiarity with containerization tools such as Docker.

Responsibilities

• Build end-to-end data pipelines and software for ML models.
• Collaborate with scientists and engineers to design and implement data infrastructure.
• Supervise or coordinate technicians and staff when needed.
• Ensure health, safety, and compliance in lab environments.

Skills

Python

BigQuery SQL

Data analysis

Collaboration

Education

Bachelor’s degree in engineering/science/related field

Tools

Docker

Job description

Stanford University in Palo Alto, CA, is seeking a Machine Learning Engineer to develop end-to-end data pipelines and modular software for ML models used in healthcare research. You will work with scientists and engineers to evaluate model performance, safety, and transparency, while guiding tool and platform choices for data projects.

The role emphasizes independent work on complex data challenges within a hybrid environment and collaboration across multidisciplinary teams.