Job Description

Digital Pathology Technician

Onsite, Vista CA 92081

W2 Contract to Possible Hire

The Digital Pathology Technician – AI/ML Support is a key technical role supporting our mission to advance cancer diagnostics through innovative digital pathology solutions. This role combines expertise in digital imaging, histological slide handling and close collaboration across laboratory, engineering, and data science teams.

In this role, you will help ensure the accuracy, consistency, and quality of scanned slides used in digital workflows and data-driven applications. You’ll support continuous improvement in slide preparation, scanning, and artifact handling processes, helping enable scalable, high-quality datasets.

This position reports to the Manager, SW Developer and is based on-site.

In this role, you will have the opportunity to:

• Procure, order, organize, and track tissue blocks and histology slides to support digital scanning workflows.
• Prepare and load slides for whole slide imaging, ensuring high-quality scans through proper calibration and scanner maintenance.
• Perform quality control (QC) on scanned slides, identifying and annotating scan-related or histological artifacts according to defined protocols.
• Collaborate with pathologists and lab staff to define, refine, and continuously improve artifact classification and annotation workflows.
• Partner with cross-functional teams, including Machine Learning (ML) and Data Science, to align on image quality standards, annotation guidelines, and model training requirements.
• Contribute to best practices for digital pathology operations and cross-functional workflows between lab and data science teams.

The essential requirements of the job include:

• Hands-on experience with digital slide scanners (e.g., Leica, Hamamatsu, Aperio), including basic imaging calibration and maintenance.
• Experience working with digital pathology or lab information systems (LIS/LIMS).
• Strong attention to detail with the ability to follow and optimize standardized protocols.
• Effective communication and collaboration skills across technical and non-technical teams.

It would be a plus if you also possess:

• Associate’s or Bachelor’s degree in Histotechnology, Biology, Medical Laboratory Science, or a related field.
• 1–3 years of experience working in a histology or pathology laboratory.
• Knowledge of histological processes including sectioning, staining, and slide preparation.
• Prior experience with digital annotation platforms (e.g., QuPath, or internal tools).
• Experience working in a regulated environment with exposure to CAP/CLIA or IVD workflows.
• Understanding of how slide quality and annotation accuracy impact machine learning performance.
• Experience in digital pathology workflows and image quality control for AI/ML or research applications.

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