About the job
Join Our Mission
At Heidi, we believe healthcare deserves a harmonious approach that prioritizes continuous and compassionate care. Our innovative AI Care Partner collaborates with clinicians to enhance patient care.
As a diverse team of healthcare professionals, engineers, designers, researchers, and creatives, we are dedicated to developing tools that allow clinicians to focus on what truly matters: their patients.
In just 18 months, we have contributed over 18 million hours back to healthcare providers, supporting 73 million patient visits across 116 countries. Currently, Heidi powers over two million patient visits each week globally.
With nearly $100 million in funding, we are expanding into the US, UK, Canada, and Europe, and partnering with leading health systems such as the NHS, Beth Israel Lahey Health, and Monash Health.
Your Role
As an integral member of our Model Platform team, you will work closely with our Engineering Manager as an AI Model Engineer. Your expertise will significantly contribute to enhancing our foundational models.
Your primary focus will be to leverage your technical skills to conduct experiments, implement advanced fine-tuning techniques (such as SFT and RLFT), and systematically enhance the performance, safety, and efficiency of our large language models (LLMs).
Key Responsibilities:
- Manage Model Fine-Tuning: Execute comprehensive fine-tuning experiments, overseeing everything from data curation to analysis and reporting.
- Collaborate Across Teams: Work with product, medical knowledge, and design teams to automate prompt engineering and develop agentic AI solutions.
- Create Innovative LLM Features: Design and implement state-of-the-art LLM functionalities using the latest tools and frameworks.
- Apply Advanced Techniques: Adapt and implement cutting-edge algorithms from research to address specific product challenges.
- Conduct Thorough Model Analysis: Analyze model behavior in detail, identify failure points, and propose data-driven or algorithmic solutions.
- Enhance Core Infrastructure: Contribute to building and refining the core training and experimentation infrastructure to accelerate research efforts.
