Machine Learning Intern

Role overview

This is a practical research-and-development internship focused on machine learning work for an AI team. The intern will contribute to building, testing, and improving ML models and AI solutions that support real healthcare use cases. The role is based in New York, NY, with onsite work required three days per week.

The internship is a full-time internship format, starts immediately, and runs through the end of summer. The intern will report to the Director of AI and collaborate closely with engineering and product teams.

About the company

Jaan Health is an AI-driven care management company that supports healthcare providers. For close to ten years, the company has used its proprietary technology to help health systems, medical groups, and ACOs provide proactive care to large patient populations that have historically been underserved.

Phamily is the company’s main technology platform. It uses clinically tested AI and user-friendly tools to help physicians and care teams manage chronic conditions, deliver personalized care between office visits, and reduce the overall cost of care. The platform is designed to help providers get fair compensation for high-quality care delivered outside the office.

What the internship involves

This internship sits at the intersection of applied research and production systems. The work will involve experimenting with modern AI methods and turning research ideas into scalable systems that can be used in real healthcare settings.

Key responsibilities

• Design and prototype new machine learning approaches, especially for NLP, LLMs, and transformer-based healthcare applications.
• Run applied experiments, evaluate results, and iterate on models to improve performance.
• Develop prompting methods, fine-tuning approaches, and retrieval pipelines.
• Convert research findings into systems that can be used in production.
• Create evaluation methods that connect model quality with healthcare outcomes.
• Partner with engineering and product teams to launch AI features.
• Work with large, real-world healthcare datasets and turn them into useful insights.
• Record methods, findings, and technical recommendations clearly.

Requirements

• Current MS or PhD candidate in Machine Learning, Computer Science, or a related discipline.
• Strong grounding in deep learning, NLP, and/or large language models.
• Hands-on experience with PyTorch, TensorFlow, or Hugging Face.
• Demonstrated ability to run experiments and draw conclusions from data.
• Strong Python skills and comfort working with messy, real-world datasets.
• Interest in turning research work into practical production impact.

Preferred background

• Experience with conversational AI.
• Exposure to LLM evaluation, fine-tuning, or retrieval-based systems.
• Experience working with healthcare data or ML in regulated environments.

Work style and culture

The company is early-stage and fast-growing, so the ideal person thrives in a high-velocity environment, takes ownership, handles ambiguity well, and stays resilient while building for scale. The team values people who can both design and execute solutions, while thinking ahead about future needs.

The culture is guided by five principles: care, curiosity, clarity, co-creation, and craftsmanship.

What you will gain

• Experience solving high-impact AI problems in healthcare.
• Ownership of projects that move from research concepts to deployed systems.
• Exposure to a fast-moving, product-oriented ML team.
• Hands-on experience in a high-growth environment.
• Interaction with executive leaders and cross-functional teams.
• Mentorship and professional development support.
• Exposure to real business challenges.
• Growth in communication, collaboration, and problem-solving.
• Stronger confidence, ownership, and business understanding.
• Opportunity to contribute to a mission-driven team working to improve healthcare at scale.

Compensation and terms

The internship pays between $30.00 and $35.00 per hour.

Equal employment opportunity: the employer is committed to inclusive hiring and does not discriminate based on race, color, religion, sex, national origin, age, disability, genetics, veteran status, sexual orientation, gender identity or expression, or any other legally protected status.