Job Function: Technology Product & Platform Management
Job Sub Function: Technical Product Management
Job Category:Scientific/Technology
All Job Posting Locations:La Jolla, California, United States of America, Spring House, Pennsylvania, United States of America
Job Description:We are seeking the best talent for a
Technical Product Owner - Digital Pathology, to be located in
Spring House, PA (US), La Jolla, CA (US) or Beerse, Belgium.
Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):
- United States (Spring House or La Jolla) - Requisition Number: R-092153
- Belgium (Beerse) - Requisition Number: R-093933
The Technology Product Owner for Digital Pathology will own the strategy, technical delivery, adoption, and support of digital pathology products, working directly with business stakeholders and technical teams across key platforms. This business technology role combines hands-on expertise in pathology imaging, data pipelines, analytics, AI/ML, and generative AI with program-level leadership to coordinate cross-functional stakeholders, vendors, and engineering teams. You will enable scientists to acquire, access, analyze, and interpret high-quality slides and imaging data reliably and at scale while identifying opportunities to use AI responsibly to accelerate research workflows and improve decision-making.
Key Responsibilities- Define and maintain an AI-enabled digital pathology product strategy and roadmap, translating scientific use cases into prioritized capabilities across image analytics, multimodal models, generative AI, workflow automation, and human-in-the-loop decision support.
- Evaluate and apply enterprise-approved large language models and AI assistants, such as Claude or comparable platforms, to accelerate requirements analysis, technical documentation, coding, scientific knowledge retrieval, and digital pathology workflow automation while protecting confidential and regulated data.
- Provide hands-on engineering work: build and maintain image processing pipelines, automation scripts, APIs, and integrations between scanners, viewers, storage, and analytics systems.
- Collaborate with data scientists and ML engineers to provision and optimize datasets for algorithm development and validation, support annotation workflows and tool integration.
- Lead responsible adoption of AI-enabled capabilities by establishing pilot criteria, user feedback loops, adoption plans, and outcome metrics such as analysis cycle time, annotation effort, model-assisted review efficiency, data reuse, and scientific decision impact.
- Ensure compliance with relevant data security, privacy, intellectual property, regulatory, and responsible AI requirements for research imaging data and AI-enabled solutions, including approved model and data usage, access controls, auditability, human oversight, bias and performance assessment, and documented risk-based validation.
QualificationsRequired:- Bachelor's degree in Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, or related field.
- 5+ years of hands-on technical experience supporting scientific research platforms (ideally with at least 2-3 years focused on digital pathology, histology imaging, or biomedical imaging systems).
- Demonstrated track record of leading technical programs or major products end-to-end in a complex organization, including rapid prototyping, evidence-based prioritization, stakeholder adoption, and scaling successful AI or data capabilities into reliable services.
- Familiarity with digital pathology/image formats and tools (examples: whole-slide imaging formats such as SVS/NDPI/OME-TIFF; libraries and tools such as OpenSlide, QuPath, ImageJ/Fiji).
- Strong software and data engineering skills: Python/R, SQL, REST APIs, containerization (Docker), CI/CD practices, and cloud environments (AWS/Azure/GCP).
- Experience integrating instrumentation (slide scanners, microscopes) with IT systems via APIs, vendor SDKs, or middleware.
- Solid understanding of databases and query languages (SQL and/or NoSQL) and metadata management for research data.
- Strong troubleshooting and root-cause analysis skills for distributed systems and imaging hardware/software.
- Excellent written and verbal communication skills; ability to translate scientific requirements into technical solutions and to drive cross-functional alignment.
- Strong AI fluency and a continuous-learning mindset, with the ability to assess emerging foundation models, computer vision methods, and AI development tools; distinguish useful capabilities from hype; communicate limitations and risks; and recommend build, buy, partner, or reuse decisions based on scientific value and total cost of ownership.
- Comfortable working directly with scientists in lab settings and translating their needs into technical requirements.
Preferred: - Advanced degree (MS/PhD) in computational biology, bioinformatics, computer sciences or related discipline.
- Experience with image analysis and ML tooling: familiarity with machine learning frameworks (TensorFlow or PyTorch) and common image pre-processing techniques.
- Experience designing and operating data pipelines and storage solutions for large image datasets; knowledge of object storage and efficient retrieval patterns.
- Hands-on experience with specific scanner ecosystems and vendor SDKs (e.g., Leica, Aperio) and viewer platforms (open-source or commercial).
- Hands-on experience with ML and MLOps frameworks and practices, including scikit-learn, TensorFlow or PyTorch, experiment tracking, model and dataset registries, reproducible training pipelines, deployment, monitoring, drift detection, retraining criteria, and model retirement.
- Familiarity with laboratory information management systems (LIMS) and integration patterns between LIMS and digital pathology systems.
- Exposure to regulatory or compliance frameworks relevant to research data (e.g., HIPAA awareness, research data governance).
- Experience building annotation tools or managing annotation workflows for pathologist/annotator teams.
- Prior experience in a pharmaceutical, biotech, or academic core facility environment.
#JNJTECH
Required Skills:Preferred Skills:The anticipated base pay range for this position is :$94,000.00 - $151,800.00
Additional Description for Pay Transparency:
Subject to the terms of their respective plans, employees are eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
• Vacation -120 hours per calendar year
• Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado -48 hours per calendar year; for employees who reside in the State of Washington -56 hours per calendar year
• Holiday pay, including Floating Holidays -13 days per calendar year
• Work, Personal and Family Time - up to 40 hours per calendar year
• Parental Leave - 480 hours within one year of the birth/adoption/foster care of a child
• Bereavement Leave - 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
• Caregiver Leave - 80 hours in a 52-week rolling period10 days
• Volunteer Leave - 32 hours per calendar year
• Military Spouse Time-Off - 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits
