Principal Machine Learning Engineer

Hologic•Newark, DE

About The Position

As a Principal Machine Learning Engineer in Hologic’s Breast and Skeletal Health division, you will play a pivotal role in designing, developing, and deploying advanced AI algorithms for next-generation medical devices. You will focus on creating and validating AI-driven solutions for breast cancer detection in breast tomosynthesis (3D mammography). Your work will have a direct impact on patient outcomes by ensuring our technologies are robust, safe, and clinically validated—upholding Hologic’s mission to deliver innovation with precision and reliability.

Requirements

Deep expertise in machine learning and deep learning, including supervised and self-supervised methods.
Mastery of cutting-edge neural network architectures and training techniques.
Strong foundation in computer vision, data preprocessing, feature engineering, and statistical analysis.
Experience with model validation and performance benchmarking.
Knowledge of software engineering best practices for building maintainable, scalable systems.
Advanced programming in Python and C++, with proficiency in ML/data science libraries (e.g., Pandas, OpenCV, XGBoost, NumPy, SciPy).
Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and cloud platforms (AWS, Azure, GCP).
Proven ability to design, implement, and optimize machine learning pipelines for large-scale, high-dimensional 3D medical imaging data.
Experience deploying and maintaining models in production environments.
Strong problem-solving skills for translating clinical requirements into technical solutions.
Excellent communication skills for technical documentation and stakeholder presentations.
Effective cross-functional collaboration with engineers, clinicians, and product managers.
Demonstrates leadership and initiative in driving complex projects from concept to deployment.
Champions a collaborative, open, and success-driven team culture.
Maintains high standards of integrity, accountability, and ethical decision-making.
Adapts quickly to evolving technologies and priorities.
Proactively seeks feedback and growth opportunities.
Shows resilience and resourcefulness in technical and regulatory challenges.
Prioritizes patient safety, data privacy, and compliance.
Inspires teams through commitment to Hologic’s mission and values.

Nice To Haves

Familiarity with FDA regulatory standards for AI in healthcare, DICOM format, digital breast tomosynthesis, and breast cancer pathology/diagnostic workflows.