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Location
In office (Marlborough)
Seniority
Principal · 10+ years exp
Visa
H-1B filings in 12 months: 30 · for this role: 5 · green card filings: 7

Confirmed on the employer's own hiring board on Nov 7, 2026. First seen by Alion on Nov 6, 2026. Hologic scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Hologic is a medical technology company headquartered in Marlborough, Massachusetts, that develops diagnostics, breast and skeletal imaging and surgical products with a focus on women's health. Founded in 1985 and listed on Nasdaq, it makes mammography and breast biopsy systems, molecular diagnostic assays and gynecological surgical devices, with manufacturing in Newark, San Diego and Alajuela in Costa Rica, and it acquired the UK breast surgery firm Endomag. It hires electrical and software engineers, chemists, clinical account managers, field service engineers, manufacturing supervisors, quality specialists and finance analysts.

At Hologic, we are driven by a singular purpose: to enable healthier lives everywhere, every day. As a global leader in women’s health, we design innovative diagnostic and imaging solutions that help detect disease earlier and improve outcomes for patients worldwide. Join a team where your work in AI and digital diagnostics directly supports clinicians in delivering better care for women.

Job Summary

Hologic is seeking a Principal Software Algorithm Engineer to design, train and validate deep learning models for cytology on the Genius™ Digital Diagnostics System. This role owns the cell-level CNN classifier, nuclear-to-cytoplasmic (NC) ratio segmentation pipeline, and the technical evidence needed to support FDA and other regulatory submissions. The engineer serves as the technical lead for model design and verification under design controls, working closely with cytopathologists, imaging scientists, regulatory and quality teams.

Key Responsibilities

  • Design, train and tune multi-class CNNs to classify cells and aggregate predictions into specimen-level diagnostic categories.
  • Develop multi-task models with shared encoders and feature heads for diagnostic class, cytomorphologic features and NC ratio category.
  • Build nucleus and cytoplasm segmentation networks to measure NC ratio and nuclear area, including overlapping cells in clusters.
  • Own the data pipeline, including patient-grouped splits, color profile application, class balance and imaging metadata.
  • Run disciplined experiments, benchmark lightweight backbones against larger reference models and define evaluation metrics and reports.
  • Collaborate with pathologists on labeling protocols, inter-observer agreement and adjudication processes.
  • Prepare design documentation, verification/validation protocols and technical content for regulatory submissions.
  • Mentor engineers and establish coding, reproducibility and MLOps standards.
  • Ensure model performance and interpretability, including Grad-CAM checks and feature outputs that align with pathologist expectations.
  • Support regulatory strategy for AI-enabled medical devices under design controls and PCCP guidance.

Qualifications

Education

  • MS or PhD in computer science, biomedical engineering, electrical engineering or a related field, or BS with equivalent experience.

Experience

  • 10+ years of software development, including 5+ years building and deploying deep learning models for computer vision.
  • Demonstrated leadership experience, with the ability to set strategic direction, influence senior stakeholders, lead cross-functional initiatives, and drive accountability and execution in a complex, matrixed organization.

Skills

  • Expert Python and PyTorch (or TensorFlow), including CNN fine-tuning, transfer learning and segmentation (e.g., U-Net, segmentation_models_pytorch).
  • Experience with imbalanced, multi-class and multi-task problems, and metrics such as per-class sensitivity, F1, kappa and AUROC.
  • Experience with medical or microscopy imaging, including color handling, stain variation and high-resolution tiling.
  • Strong discipline in data splitting, leakage prevention, experiment tracking and reproducible training.
  • Clear written communication for technical reports and design documentation.
  • Preferred: digital pathology or cytology AI experience (ideally urine cytology); experience with FDA 510(k), De Novo, PMA or EU IVDR; familiarity with IEC 62304, ISO 13485, ISO 14971, 21 CFR Part 820 and FDA PCCP guidance.
  • Preferred: ICC color management, stain deconvolution and scanner color calibration; cell instance segmentation tools (StarDist, Cellpose) and annotation tools (QuPath, CVAT, napari).
  • Preferred: model optimization for edge or embedded inference (quantization, ONNX, TensorRT) and experience leading or technically guiding a small team.

Why join Hologic?

We are committed to making Hologic the destination for top talent. 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.

The annualized base salary range for this role is $157,000 - $220,000 and is bonus eligible. Final compensation packages will ultimately depend on factors including relevant experience, skillset, knowledge, 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.

Hologic is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.

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