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
You might be a fit if you:
Think in systems — mapping feedback loops, interdependencies, and second-order effects comes naturally to you
Are motivated by purpose-driven work, particularly at the intersection of technology and healthcare
Believe technology should be a force for good and are drawn to the Public Benefit Corporation model
Hold yourself and your work to a values-first standard, not just a deliverables-first one
Lead with first principles and are comfortable questioning assumptions others take for granted
See complexity as an invitation, not an obstacle — you thrive when problems are messy and interconnected
Care about the downstream effects of what you build — on users, on systems, on society
Operate with intellectual humility — always learning, always open to being wrong
Compensation:
Commensurate with experience and level.
About System
We aspire to help the world see itself differently and build a more responsible and values-driven model of a tech company. We are backed by top-tier VCs in Silicon Valley and New York and leading angel investors and founded by the former VP Data at Spotify. To learn more about what motivates our social mission, we invite you to read our blog here .
We believe in the power of autonomous, interdisciplinary, and diverse teams; in agile development; and in leading with values, first principles, and clear high-level priorities backed by data. We believe in cultivating a growth mindset for our team — always learning, improving, being challenged, and having opportunities for professional and personal development.
System Inc. is an equal opportunity employer. We are proud to foster a workplace, in person and online, free from discrimination. We strongly believe that diversity of experience, perspectives, and backgrounds will lead to a better environment for our employees and a better product for our users. We are committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Job applicants must be legally authorized to work in the United States of America and must maintain ongoing work authorization during employment.