Data & AI/ML Engineer — Healthcare Data Systems

System; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

System is a Public Benefit Corporation building scalable data and AI infrastructure for healthcare. The Data & AI/ML Engineer will design pipelines, deploy ML models, and develop AI-ready data infrastructure in production across cloud platforms.

The ideal candidate brings 4+ years in data/ML engineering, strong Python and SQL, and experience with Spark, dbt, or Airflow, plus familiarity with containerization and healthcare data workflows.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 4+ years of experience in data engineering, ML engineering, or a related discipline.
• Strong proficiency in Python and SQL; experience with Spark, dbt, or Airflow a plus.
• Experience building and maintaining cloud data infrastructure (AWS, GCP, or Azure).
• Understanding of ML lifecycle management, model versioning, and deployment patterns.
• Comfort with systems design principles applied to data-intensive architectures.

Responsibilities

• Design and maintain scalable data pipelines and ETL/ELT workflows.
• Build and operate infrastructure for training, deploying, and serving ML models in production.
• Develop feature stores, vector databases, and other AI-enabling data infrastructure.
• Ensure reliability, low latency, and high availability of data systems.
• Partner closely with Research and Data Science to move findings into production.
• Implement monitoring and observability for data and model health.
• Contribute to infrastructure as code practices and documentation on cloud platforms.

Skills

Python

SQL

Systems design

Education

Bachelor’s or Master’s in CS/Engineering

Tools

Spark

dbt

Airflow

Job description

System is a Public Benefit Corporation building scalable data and AI infrastructure for healthcare. The Data & AI/ML Engineer will design pipelines, deploy ML models, and develop AI-ready data infrastructure in production across cloud platforms.

The ideal candidate brings 4+ years in data/ML engineering, strong Python and SQL, and experience with Spark, dbt, or Airflow, plus familiarity with containerization and healthcare data workflows.