Senior Machine Learning Engineer - Medical Imaging

About the Role

We are seeking a Senior Machine Learning Engineer - Medical Imaging to join our innovative team at MD Anderson Cancer Center. In this remote role, you will play a pivotal part in shaping the future of clinical AI by developing and deploying advanced imaging models that directly impact patient care.

What You'll Do

• Own the full lifecycle of medical imaging ML models, from problem definition and model development to deployment and ongoing performance monitoring.
• Collaborate with multidisciplinary teams, including clinicians, data scientists, and operational leaders, to translate clinical imaging use cases into deployable AI solutions.
• Design and execute post-deployment monitoring strategies to detect and mitigate model degradation due to distribution shifts or scanner changes.
• Participate in formal governance, release, and incident review processes, ensuring responsible AI practices and compliance with regulatory standards.
• Mentor junior team members and contribute to best practices in machine learning workflows.

Requirements

• Bachelor's degree in Computer Science, Data Science, or a related field; Master’s degree or PhD preferred.
• Five years of experience in machine learning engineering, with a focus on medical imaging.
• Deep proficiency in Python and PyTorch, with experience in deploying ML models in regulated environments.
• Experience with DICOM workflows and building imaging data pipelines.
• Strong understanding of healthcare data privacy requirements and model validation strategies.

Nice to Have

• Experience operating medical imaging ML systems across multiple sites or protocols.
• Familiarity with containerized ML workloads on cloud platforms like Azure using Kubernetes.
• Experience in engaging with clinical stakeholders to communicate model performance and risks.

What We Offer

• Competitive salary ranging from $146,500 to $219,500, commensurate with experience.
• Comprehensive benefits package including medical, dental, and retirement plans.
• Generous paid time off and educational opportunities.
• Relocation assistance available for candidates moving to Texas.
• A collaborative and innovative work environment focused on advancing patient care through technology.