Our story
We’re a fast growing, Series A stage health AI company building a clinical operating system for MSK practices. We are revenue generating and are looking to carefully expand the team to help us scale to 1,000,000 patients and beyond!
The team is headquartered in NYC with a satellite office in Vancouver, BC. Much of our engineering team is remote - distributed throughout the US and Canada.
We live in Notion docs, Slack channels and Github with weekly meetings over Zoom. Meetings may feature honorary advisors, MedTech execs, and, if we’re lucky, Will’s cat or our Chief Pup Officer.
As Flagler continues to grow, there is a unique opportunity to build the foundations of data and infrastructure to help the product and company reach our full potential. This is where you come in — to design and build reliable, trusted, and timely analytics that accelerate the decision-making process of key product and business functions. You will have a strong impact on the roadmap and growth trajectory of our company.
What You Will Do
- Develop LLM and other ML-based approaches for chart abstraction from both unstructured and structured healthcare data.
- Design, build, deploy, and improve machine learning models for operational analytics to help us optimize clinical operations
- Design and develop Reinforcement Learning models that leverage physician feedback and patient outcomes to continuously improve clinical performance and AI safety
Required Qualifications
- Research, develop, and productionize LLM-powered machine learning methods for extracting insights from longitudinal clinical data (both unstructured and structured).
- Design, build, deploy, and improve machine learning models for operational analytics to help us optimize clinical operations
- Design and develop Reinforcement Learning models that leverage physician feedback and patient outcomes to continuously improve clinical performance and AI safety
- Proven experience in data science, including a proven track record of successful projects in healthcare or operation analytics
- Strong programming skills in Python, and fluency with modern data science and ML/NLP libraries (PyTorch, HuggingFace, etc.).
- Knowledge of both statistical and modern deep learning (e.g. transformer) techniques and architectures.
Hiring Process
Due to the high volume of applications, we only reach out to candidates selected for interviews. We do not have online leetcode assessments as an initial filter, so we only reach out to very few candidates for initial introduction.
