Senior Scientist II, Computational Pathology, Precision Medicine Pathology

AbbVie
AbbVie logo
Location
South San Francisco, CA
Job Type
Full-time
Posted
August 22, 2026
Views
5

Job Description

Company Description

About AbbVie

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Job Description

AbbVie Precision Medicine Pathology organization is committed to driving tissue based translational and biomarker efforts for our pre-clinical and clinical stage programs. We are seeking a talented and motivated Machine Learning (ML) Scientist to develop and apply advanced Artificial Intelligence (AI) techniques for analyzing complex histopathology and spatial omics datasets. This is a hands-on role ideal for candidates who are passionate about learning, collaborating, and driving innovation in the exciting intersection of machine learning, digital pathology, and precision medicine.

As a computational pathology scientist, you will be an integral part of a highly cross-functional team, working closely with colleagues from pathology laboratories and collaborating with research pathologists and assay scientists. You will engage with investigators involved in both discovery and late-stage research across a spectrum of disease areas, including oncology, cancer immunotherapy, immunology, and neuroscience, leveraging your AI expertise to advance our team's research objectives.

Key Responsibilities

  • Develop, train, and validate machine learning models for tissue image analysis, including segmentation, object detection, and classification.
  • Apply advanced techniques such as deep learning and representation learning to solve key challenges in digital pathology.
  • Curate and maintain large-scale pathology datasets, ensuring data quality and integrity for robust model training and evaluation.
  • Develop and implement tools and pipelines for data preprocessing, feature engineering, and model deployment.
  • Collaborate with pathologists, biologists, statisticians, data analysts, and fellow engineers to integrate machine learning solutions into existing workflows.
  • Assist in external collaborations with research partners to enhance project outcomes and foster innovation.
  • Assist in evaluating histopathology and spatial omics datasets to identify biomarkers that inform patient stratification and companion diagnostic efforts.
  • Stay updated on the latest developments in AI, machine learning, and digital pathology techniques, and bring these insights to ongoing projects.

Qualifications

Required Qualifications

  • Ph.D. in Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, or related field with an emphasis on computer vision or machine learning; OR M.S. with 5+ years of relevant industry experience.
  • Experience in image analysis techniques, including segmentation, object detection, and classification, evidenced by publications, open-source projects, or product development.
  • Proficiency in programming languages like python and demonstrated experience using computer vision libraries such as OpenCV and ML frameworks like TensorFlow and PyTorch.
  • Familiarity with MLOps practices, including deployment, monitoring, and lifecycle management of machine learning models in production environments.
  • Familiarity with cloud computing platforms and scalable AI/ML pipelines (e.g., AWS, Azure, GCP).
  • Excellent communication skills, including the ability to contribute to collaborative projects and explain technical concepts to interdisciplinary teams.
  • Strong problem-solving skills and demonstrated creative approaches to overcoming challenges.

Preferred Qualifications

  • Exposure to digital pathology or biomedical imaging, such as histopathology, microscopy, or tissue imaging datasets.
  • Experience with spatial omics data or integrating molecular data with image analysis.
  • Working knowledge of techniques in precision medicine, biomarker discovery, or personalized treatment strategies is a plus.
  • Familiarity with cell and molecular biology concepts in fields like oncology, immunology, or cancer immunotherapy, or an eagerness to learn.

Company Description

About AbbVie

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Job Description

AbbVie Precision Medicine Pathology organization is committed to driving tissue based translational and biomarker efforts for our pre-clinical and clinical stage programs. We are seeking a talented and motivated Machine Learning (ML) Scientist to develop and apply advanced Artificial Intelligence (AI) techniques for analyzing complex histopathology and spatial omics datasets. This is a hands-on role ideal for candidates who are passionate about learning, collaborating, and driving innovation in the exciting intersection of machine learning, digital pathology, and precision medicine.

As a computational pathology scientist, you will be an integral part of a highly cross-functional team, working closely with colleagues from pathology laboratories and collaborating with research pathologists and assay scientists. You will engage with investigators involved in both discovery and late-stage research across a spectrum of disease areas, including oncology, cancer immunotherapy, immunology, and neuroscience, leveraging your AI expertise to advance our team's research objectives.

Key Responsibilities

  • Develop, train, and validate machine learning models for tissue image analysis, including segmentation, object detection, and classification.
  • Apply advanced techniques such as deep learning and representation learning to solve key challenges in digital pathology.
  • Curate and maintain large-scale pathology datasets, ensuring data quality and integrity for robust model training and evaluation.
  • Develop and implement tools and pipelines for data preprocessing, feature engineering, and model deployment.
  • Collaborate with pathologists, biologists, statisticians, data analysts, and fellow engineers to integrate machine learning solutions into existing workflows.
  • Assist in external collaborations with research partners to enhance project outcomes and foster innovation.
  • Assist in evaluating histopathology and spatial omics datasets to identify biomarkers that inform patient stratification and companion diagnostic efforts.
  • Stay updated on the latest developments in AI, machine learning, and digital pathology techniques, and bring these insights to ongoing projects.

Qualifications

Required Qualifications

  • Ph.D. in Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, or related field with an emphasis on computer vision or machine learning; OR M.S. with 5+ years of relevant industry experience.
  • Experience in image analysis techniques, including segmentation, object detection, and classification, evidenced by publications, open-source projects, or product development.
  • Proficiency in programming languages like python and demonstrated experience using computer vision libraries such as OpenCV and ML frameworks like TensorFlow and PyTorch.
  • Familiarity with MLOps practices, including deployment, monitoring, and lifecycle management of machine learning models in production environments.
  • Familiarity with cloud computing platforms and scalable AI/ML pipelines (e.g., AWS, Azure, GCP).
  • Excellent communication skills, including the ability to contribute to collaborative projects and explain technical concepts to interdisciplinary teams.
  • Strong problem-solving skills and demonstrated creative approaches to overcoming challenges.

Preferred Qualifications

  • Exposure to digital pathology or biomedical imaging, such as histopathology, microscopy, or tissue imaging datasets.
  • Experience with spatial omics data or integrating molecular data with image analysis.
  • Working knowledge of techniques in precision medicine, biomarker discovery, or personalized treatment strategies is a plus.
  • Familiarity with cell and molecular biology concepts in fields like oncology, immunology, or cancer immunotherapy, or an eagerness to learn.

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​

  • The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. ​
  • We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.​
  • This job is eligible to participate in our long-term incentive programs.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.​

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled.

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html

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Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The position is located in South San Francisco, CA. The job posting does not specify a remote or hybrid work-mode policy, indicating it is an on-site role at this location.
What are the required qualifications and experience level for this role?
You need a Ph.D. in Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, or a related field focusing on computer vision/machine learning, OR an M.S. with 5+ years of relevant industry experience. Required skills include image analysis, Python proficiency, OpenCV, TensorFlow/PyTorch, MLOps practices, and cloud computing platforms.
What are the key responsibilities of this position?
You will develop, train, and validate machine learning models for tissue image analysis, curate large-scale pathology datasets, and implement data preprocessing pipelines. You will also collaborate with multidisciplinary teams, assist in external research collaborations, and evaluate datasets to identify biomarkers for patient stratification.
What benefits are offered with this position?
AbbVie offers a comprehensive benefits package to eligible employees, which includes paid time off (vacation, holidays, and sick leave), medical, dental, and vision insurance, and a 401(k) plan. Additionally, this role is eligible to participate in the company's long-term incentive programs.

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Explore AbbVie

Research the company before you apply.

  • 19 open roles
  • Verified H-1B salary data
  • Clinical-trial hiring momentum
  • Culture, benefits & locations
View company profile

Job Information

Source: manual
AI Relevance: 92/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
abbvie machine learning deep learning artificial intelligence bioinformatics computational biology immunology oncology clinical

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