Machine Learning Engineer

Summary

Join Flatiron Health as a Machine Learning Engineer and contribute to our mission of improving lives through cancer research. You will develop and validate machine learning models to extract clinically relevant information from medical notes. This role involves collaborating with cross-functional teams, including data scientists, oncologists, and software engineers. You will work on projects from initial scoping to production and delivery, ensuring models generate sound scientific insights. The position requires 3+ years of experience in ML, with a strong background in applying ML to real-world problems and experience with NLP. Flatiron offers a hybrid work model and a comprehensive benefits package.

Requirements

• Have 3+ years of relevant working experience in a technical capacity, with a focus on ML
• Have a strong background in applying ML to solve real-world problems and a solid grasp of the underlying statistical fundamentals of ML
• Have collaborated with other technical team members in a production development environment using formal version control, Python, and SQL
• Have led cross-functional initiatives and excel at influencing decision-making without authority

Responsibilities

• Develop and validate models to solve applied clinical problems and help build towards our vision of the future of machine learning at Flatiron
• Interface with internal scientific stakeholders and customers to understand what data they need to conduct high quality research
• Build models to turn raw clinical data into high quality research variables, drawing on your knowledge of LLMs, traditional ML, and NLP techniques to determine the right methods to use for a given problem
• Work with quantitative scientists and oncologists to validate that your models can be used to generate sound scientific insights
• Collaborate with other Data Scientists to accelerate our ML capabilities and develop novel approaches to clinical data extraction from unstructured health records
• Work cross-functionally with software engineers to productionize, scale, and monitor your models

Preferred Qualifications

• Have experience with deep learning and LLMs
• Have ML experience in a healthcare setting
• Have experience with the risks of bias in machine learning, health equity research/analysis or have worked with underrepresented groups in a clinical research setting

Benefits

• Work/life autonomy via flexible work hours and flexible paid time off
• Comprehensive compensation package
• 401(k) contribution to help you reach your retirement planning goals
• Financial health resources including 1:1 financial advice
• Mental well-being tools and services
• Parental benefits and policies including family-building care and generous leave
• Path to parenthood programs supporting fertility, adoption and surrogacy
• Travel support for safe healthcare services