Machine Learning Engineer

About Radformation Radformation is transforming the way cancer clinics deliver care. Our innovative software automates and standardizes radiation oncology workflows, enabling clinicians to plan and deliver treatments faster, safer, and more consistently, so patients everywhere can receive the same high-quality care. Our software focuses on three key areas: Time savings through automation. Error reduction through automated systems. Increased quality care through advanced algorithms and workflows. We are a fully remote, mission-driven team united by a shared goal: to reduce cancer’s global impact and help save more of the 10 million lives it claims each year. Every line of code, every product release, and every conversation with our customers brings us closer to ensuring no patient’s treatment quality depends on where they live. Why This Role Matters In this role you will help advance Radformation’s AI-driven radiotherapy products by building and improving machine learning models that directly impact clinical workflows and patient outcomes. You will work closely with AI, cloud, research, and product teams to develop scalable data pipelines, improve model performance, and support regulatory submissions for medical device software. Responsibilities Include: Design, build, and maintain robust ETL pipelines to support AI model development and deployment. Develop, train, and optimize machine learning models used in radiotherapy software. Collaborate with product and research teams to bring new AI-driven features and algorithms into production. Support FDA submissions by contributing to documentation, validation, and regulatory processes. Participate in design reviews, risk analyses, and cross-functional discussions to ensure safe and effective products. Mentor junior engineers and data scientists and contribute to a collaborative team environment. Required Experience: MS in Computer Science, Mathematics, Statistics, or a related field with 3+ years of experience. Exp