Staff Machine Learning Engineer

Overview

We are partnering with a fast-growing healthcare technology company at the forefront of AI-driven medical innovation. With strong clinical validation, regulatory progress, and real-world adoption, the organization is advancing how medical imaging is used to predict disease risk and enable earlier, more proactive care.

This is a high-impact, senior technical role focused on developing next-generation machine learning models for medical imaging. You will play a key role in shaping the company’s ML strategy, advancing core algorithms, and setting best practices for model development in a regulated environment.

What You’ll Do

• Lead the research and development of state-of-the-art deep learning models for medical imaging applications
• Design and implement scalable training pipelines for large-scale imaging datasets
• Drive model performance through experimentation, architecture innovation, and rigorous evaluation frameworks
• Translate clinical and scientific requirements into production-ready ML solutions
• Collaborate cross-functionally with data scientists, engineers, and clinical stakeholders
• Mentor and provide technical leadership to ML engineers and data scientists
• Partner with infrastructure teams to optimize GPU utilization, training efficiency, and deployment workflows
• Contribute to scientific publications and support intellectual property development

What You Bring

Required

• PhD with 4+ years of industry experience, or Master’s with 7+ years in Machine Learning, AI, or a related field
• Deep expertise in machine learning and self-supervised learning methods
• Strong programming skills in Python and PyTorch
• Experience building and scaling ML systems in cloud environments (AWS preferred)
• Hands-on experience with medical imaging data (DICOM) and preprocessing pipelines
• Proven track record of developing and deploying ML models in healthcare, biotech, or other regulated industries
• Strong communication skills and ability to collaborate across technical and clinical teams

Preferred

• Experience with mammography or breast imaging
• Familiarity with FDA regulatory processes for Software as a Medical Device (SaMD)
• Experience with ML orchestration tools (e.g., Metaflow or similar)
• Expertise in distributed training (multi-GPU/multi-node) and performance optimization
• Publications in leading ML or medical imaging conferences (e.g., NeurIPS, ICML, MICCAI)
• Experience with foundation models, transfer learning, or domain adaptation in medical imaging