Machine Learning Engineer (W/M/D)

We’re looking for a Machine Learning Engineer to help us accomplish our mission to improve and extend lives by learning from the experience of every person with cancer. Flatiron Health is a healthtech company using data for good to power smarter care for every person with cancer, around the world. Our multidisciplinary teams include oncologists, data scientists, software engineers, epidemiologists, product experts and more. At Flatiron, we’re advancing the use of machine learning, generative AI, and natural language processing to extract clinically relevant information from unstructured medical notes for use in oncology research. The Data Curation team is helping to build these next generation research data products, developing and applying ML models to capture a complete picture of the patient journey As part of our team, you will develop and validate models to solve applied clinical problems and help build towards our vision of the future of machine learning at Flatiron. Engaging with a cross-functional group of stakeholders across our teams in Europe, Japan, and the US you will contribute to model development projects from scoping through to productionization and delivery. 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. You're a product-focused data scientist, with experience in leveraging ML and NLP to solve real-world problems. You have 3+ years of relevant working experience in a technical capacity, with a focus on ML. You have a strong background in applying ML to solve real-world problems and a solid grasp of the underlying statistical fundamentals of ML. You have collaborated with other technical team members in a production development environment using formal version control, Python, and SQL. You have ML experience in a healthcare setting. You 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.