Senior Machine Learning Engineer at Hologic, Inc.

Newark, Delaware, United States -

Full Time

Start Date

Immediate

Expiry Date

23 May, 26

Salary

173300.0

Posted On

22 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI Algorithms, Breast Imaging, Digital Breast Tomosynthesis, ML Pipeline, Deep Learning, Computer Vision, Model Validation, Python, PyTorch, TensorFlow, Cloud Platforms, Software Engineering, DICOM, Regulatory Submissions, MLOps

Industry

Medical Equipment Manufacturing

Description

Role Summary As a Senior Machine Learning Engineer within Hologic’s Breast & Skeletal Health division, you will design, develop, and deploy advanced AI algorithms for next‑generation medical imaging devices. A key focus of this role is building and validating AI‑driven solutions for breast cancer detection in breast tomosynthesis (3D mammography). Your work will directly impact patient outcomes by ensuring our AI solutions are accurate, robust, safe, and clinically validated, supporting Hologic’s mission to improve women’s health through innovative, high‑quality technologies. Location: Santa Clara, CA | Newark, DE | Remote (US) What You’ll Do Design and develop ML/AI models for breast imaging, with a focus on digital breast tomosynthesis (DBT) and related modalities. Own the end‑to‑end ML pipeline: data preparation, feature engineering, model training, evaluation, deployment, and monitoring in production environments. Work with large‑scale medical imaging datasets, including DICOM images, to build high‑performing and reliable models. Implement and optimize deep learning architectures (e.g., CNNs and related vision models) for detection, classification, and related tasks in breast imaging. Validate and benchmark models using appropriate metrics, cross‑validation, test sets, and clinically relevant performance measures. Collaborate with cross‑functional teams (engineering, clinical, regulatory, and product) to translate clinical needs and business requirements into robust ML solutions. Contribute to design and documentation needed for regulatory submissions and clinical validation, following FDA and other relevant guidelines for AI in healthcare. Ensure code quality and reliability, applying good software engineering practices (testing, version control, code reviews, documentation). Mentor junior engineers and scientists, sharing best practices in ML, deep learning, and software development. Required Qualifications Experience: 5+ years of hands‑on experience in machine learning, applied AI, or ML engineering, ideally with exposure to computer vision or medical imaging. Education: Bachelor’s degree in a related field preferred (e.g., Computer Science, Electrical/Computer Engineering, Data Science, Mathematics, Statistics, Biomedical Engineering, or similar). Advanced degree (Master’s or PhD) is a plus but not required. Technical Skills: Strong understanding of machine learning and deep learning principles, including supervised learning and, ideally, self‑supervised or semi‑supervised methods. Solid knowledge of neural network architectures and training techniques, particularly for computer vision (e.g., CNNs, modern vision architectures). Foundation in computer vision techniques, data preprocessing, feature engineering, and statistical analysis. Experience with model validation and performance benchmarking, including selecting appropriate metrics and designing experiments. Strong programming skills in Python (required); C++ experience is a strong plus. Proficiency with ML/data science libraries and tools such as NumPy, SciPy, Pandas, OpenCV, scikit‑learn, XGBoost. Hands‑on experience with deep learning frameworks such as PyTorch and/or TensorFlow. Experience designing and implementing scalable ML pipelines, including training, inference, and monitoring. Experience with cloud platforms (e.g., AWS, Azure, or GCP) for training and/or deploying ML models. Familiarity with software engineering best practices, including modular design, testing, debugging, version control (e.g., Git), and CI/CD concepts. Preferred / Bonus Qualifications Familiarity with the DICOM format and medical imaging workflows, ideally including digital breast tomosynthesis (DBT). Understanding of breast cancer pathology, radiology workflows, and how mammography is used in clinical practice. Experience working under FDA regulatory standards or similar frameworks for AI/ML in healthcare, including validation protocols, documentation, and risk management. Experience contributing to regulated medical device software or products subject to 510(k)/PMA submissions. Exposure to MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker, model monitoring, experiment tracking). Soft Skills & Behaviors Ability to translate complex technical concepts into clear language for clinical, product, and business stakeholders. Strong problem‑solving skills and a practical mindset focused on delivering reliable, real‑world solutions. Demonstrated ability to work independently while also collaborating effectively in cross‑functional teams. Experience mentoring or guiding junior team members and contributing to team standards and best practices. High level of ownership, attention to detail, and commitment to quality, especially given the impact on patient care. So why join Hologic? We are committed to making Hologic the company where top talent comes to grow. For you to succeed, we want to enable you with the tools and knowledge required and so we provide comprehensive training when you join as well as continued development and training throughout your career. We offer a competitive salary and annual bonus scheme, one of our talent partners can discuss this in more detail with you. If you have the right skills and experience and want to join our team, apply today. We can’t wait to hear from you! The annualized base salary range for this role is $110,800 - $173,300 and is bonus eligible. Final compensation packages will ultimately depend on factors including relevant experience, skillset, knowledge, geography, education, business needs and market demand. Agency and Third-Party Recruiter Notice: Agencies that submit a resume to Hologic must have a current executed Hologic Agency Agreement executed by a member of the Human Resource Department. In addition Agencies may only submit candidates to positions for which they have been invited to do so by a Hologic Recruiter. All resumes must be sent to the Hologic Recruiter under these terms or they will not be considered. As part of our commitment to a fair and accurate evaluation of each candidate's qualifications, we require all applicants to refrain from using AI tools, such as generative AI or automated writing assistance, during any stage of the interview process. Responses influenced by AI may result in disqualification. We appreciate your understanding and cooperation in ensuring a transparent and equitable selection process. Hologic, Inc. is proud to be an Equal Opportunity Employer inclusive of disability and veterans. #LI-DS1 #remote

Responsibilities

The Senior Machine Learning Engineer will design, develop, and deploy advanced AI algorithms, focusing on building and validating AI-driven solutions for breast cancer detection in 3D mammography. Responsibilities include owning the end-to-end ML pipeline, from data preparation to production deployment and monitoring, while collaborating with cross-functional teams.