About the Role
Welcome systems thinkers. System builds software to help the world see and solve anything as a system, starting in healthcare. We are a Public Benefit Corporation driven by purpose and shaped by values. We hire systems thinkers who are motivated by our purpose, share our values, and have the skills to advance our mission. At System, this means designing the pipelines, platforms, and model-serving systems that power our healthcare data products — reliably, responsibly, and at production grade.
As a Data & AI/ML Engineer at System, you will:
- 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
The ideal candidate has:
- 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
Bonus if you have:
- Experience with containerization and orchestration (Docker, Kubernetes)
- Familiarity with knowledge graphs, graph databases, or semantic data models
- Experience with data migrations while maintaining service availability
- Background working with clinical or healthcare data
- Exposure to LLMOps or AI governance frameworks