Machine Learning Engineer, Radformation

• BS in computer science, mathematics, statistics, or related field with 3+ years of experience, or MS with 1+ years of experience
• Expert programming skills in Python
• Experience with other high-level languages such as C#, C++, or Java (desirable)
• Fluent with PyTorch and TensorFlow
• Hands-on experience with building, training, and tuning machine learning models
• Experience building convolutional neural networks (CNNs), particularly U-Net
• Proficient with code repositories such as Bitbucket, GitHub, or Azure DevOps
• Strong knowledge of Git for version control
• You are a clear communicator and believe the team succeeds or fails together
• You are highly motivated with strong attention to detail
• You are adaptable and thrive in a fast-paced, evolving environment
• You take ownership of your work and have strong prioritization skills
• You are committed to improving the patient experience

Desirable

• In this role you will design and implement machine learning models that power Radformation’s efficiency and automation software for cancer clinics
• You will build and test AI models, maintain data ETL pipelines, and support regulatory submissions
• By improving automation and clinical workflows, you will help ensure patients receive safer, faster, and more consistent cancer treatments
• Write and maintain ETL pipelines for clinical and imaging data
• Build, train, and test machine learning models to support oncology workflows
• Support FDA submissions by contributing to documentation and testing
• Participate in design reviews, risk and hazard analyses, and other formal processes
• Collaborate with the cloud team to troubleshoot deployed systems
• Work closely with the AI team to address model issues and propose improvements
• Attend daily stand-ups and related project meetings