AI/ML Engineering Co-op
Zus Health
Internship
On-site
Boston, Massachusetts, United States
Artificial Intelligence
Who we are
Zus is a shared health data platform designed to accelerate healthcare data interoperability by providing easy-to-use patient data via API, embedded components, and direct EHR integrations. Founded in 2021 by Jonathan Bush, co-founder and former CEO of athenahealth, Zus partners with HIEs and other data networks to aggregate patient clinical history and then translates that history into user-friendly information at the point of care. Zus's mission is to catalyze healthcare's greatest inventors by maximizing the value of patient insights - so that they can build up, not around.
AI at Zus allows personalized, coordinated healthcare driven by information that is comprehensive, accessible, and timely. Zus is NOT an AI company but many of its product features are AI driven.
What we’re looking for…
We are looking for an eager software engineering co-op to help build the next generation of healthtech tools. This co-op will be part of the AI group. This group has members embedded in the product teams and also works independently on proof-of-concept projects. The ideal candidate will be able to contribute in either situation.
In your role as an AI/ML Engineer Co-op, you will, under the guidance of senior AI group members, be responsible for conducting research to explore new methodologies and techniques, and integrating them into our product offerings. You will develop prototypes to test and improve upon your innovations and develop feedback mechanisms to improve models with human oversight. You will work with software engineers to help deliver CI/CD pipelines, and automate workflows to ensure reliable and scalable model operations. You will be responsible for presenting your learnings and helping the team leverage these methods and techniques.
As part of our team, you will
- Algorithm & Experimentation: Formulate hypotheses, build rapid prototypes, and run experiments
- Evaluation & Diagnostics: Design task-specific metrics and effective methods for their estimation
- Collaboration: Work cross-functionally with engineers, product managers, and other AI group members
- End-to-End Ownership: Take prototypes to production, collaborating with engineers to deploy, and continually monitor and evaluate models
You're a good fit because you have
- Hands-on experience with LLMs and classical ML methods (must-have)
- Hands-on experience with agentic frameworks and tools such as LangGraph, Strands, LangFuse, MCP, etc.
- Proficiency in Python (must-have)
- Hands-on experience designing offline or online experiments: crafting task-specific metrics, computing bootstrapped confidence intervals, and conducting slice-based error analysis
- Familiarity with cloud services (e.g., AWS, GCP, Azure)
- Demonstrated curiosity—comfortable jumping into unfamiliar domains, papers, or codebases and learning fast
- Strong verbal/written skills—able to explain complex ML concepts to diverse stakeholders
- Demonstrated ability to work effectively in a collaborative team environment
It's a bonus if you have
- Hands-on experience with LLMs or classical ML methods in production environments
- Experience partnering with software engineers to ship, monitor, and iterate on AI/ML systems in production
- Healthcare domain experience (claims, EHR, clinical NLP)
- Bachelor's degree in Computer Science
$30 - $30 an hour
You should be located in the Boston, MA, area and willing to join us in the office or regularly meet with a local mentor for collaborative work. This role will start in January and run through June.
We will offer you...
• Competitive compensation that reflects the value you bring to the team
• Opportunity to work alongside a passionate team that is determined to help change the world (and have fun doing it).
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.