Senior Principal AI/ML Scientist, Computational Imaging

Amgen•Thousand Oaks, CA

22h

About The Position

Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Senior Principal AI/ML Scientist, Computational Imaging What you will do Let’s do this. Let’s change the world. Biomarkers and diagnostics are central to understanding how our therapeutics work and identifying patients that benefit most from these therapies. Accordingly, the Precision Medicine (PMED) function plays a critical role in advancing our drug development programs and is accountable for the development and execution of biomarkers and diagnostics strategy across our pipeline. The PMED Center for Technology and Innovation group is responsible for developing innovative biomarker assay and computational technologies that advance precision medicine objectives across therapeutic areas. We are currently seeking an AI/ML imaging expert to join our growing Computational Imaging and Digital Biomarkers team. The Senior Principal Scientist, Computational Imaging, will serve as a technical leader and hands-on scientific contributor in the development and application of advanced AI/ML methods for medical imaging, with a focus on digital pathology and/or radiology. This role is responsible for leading complex imaging AI efforts and delivering high-impact models that support biomarker discovery, patient stratification, disease characterization, and outcome prediction. The successful candidate will bring deep expertise in custom AI model development, particularly in leveraging public and proprietary foundation models to develop novel segmentation, classification, and predictive models. This role operates in a matrixed environment, partnering closely with translational pathology, clinical imaging, clinical biomarkers, and computational biologist stakeholders, while mentoring junior scientists and influencing external collaborations. This position will report directly to the Executive Director of Computational Imaging and Digital Biomarkers. In this vital role you will successfully partner with cross-functional stakeholders to drive development and implementation of imaging-based biomarkers and diagnostics.

Requirements

Doctorate degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Computational Biology, or a related quantitative field and 3 years of related experience Or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Computational Biology, or a related quantitative field and 6 years of related industry experience Or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Computational Biology, or a related quantitative field and 8 years of related industry experience

Nice To Haves

Demonstrated deep technical expertise in developing custom AI/ML models for medical imaging.
Strong experience in digital pathology and/or radiology, including whole-slide images and/or modalities such as CT, MRI, or PET.
Expertise in foundation model usage, including pre-training, fine-tuning, and domain adaptation for imaging-based tasks.
Advanced knowledge of modern computer vision and ML techniques, including: CNNs, U-Net–based architectures, Vision Transformers Self-supervised, weakly supervised, and few-shot learning Multimodal and representation learning approaches
Proficiency in Python and deep learning frameworks such as PyTorch and/or TensorFlow.
Demonstrated ability to communicate complex technical concepts clearly and influence scientific decision-making.
Strong record of scientific contributions (e.g., publications, patents, deployed models, or platform capabilities).
Demonstrated evidence of setting and implementing technical or scientific strategies for complex AI/ML or computational imaging initiatives, including defining problem statements, selecting modeling approaches, and driving execution to measurable scientific or translational outcomes.
Strong publication record in AI/ML, with particular emphasis on applications to drug development, biomarker discovery, patient stratification, or translational research; contributions to high-impact journals or top-tier AI/medical imaging conferences strongly preferred.
Experience working with integrated imaging, clinical, and molecular datasets.
Familiarity with MLOps, scalable training, and model lifecycle management.
Experience with cloud or HPC environments (e.g., AWS, Azure, GCP, SLURM), containerization, and distributed training.
Prior experience leading significant components of cross-functional or external collaboration

Responsibilities

Technical Leadership & Execution Lead the design, development, training, and validation of AI/ML models for digital pathology and/or radiology applications.
Define technical direction for custom AI/ML model development, including architecture selection, training paradigms, validation strategies, and performance benchmarks.
Develop custom deep learning architectures and workflows for segmentation, classification, representation learning, and prediction tasks.
Leverage and adapt foundation models (e.g., vision transformers, multimodal and self-supervised models), including fine-tuning and domain adaptation using proprietary datasets.
Data Science & Modeling Excellence Extract insights from large-scale imaging datasets, including whole-slide images and radiology modalities (CT, MRI, PET).
Apply advanced computer vision and machine learning methods, including CNNs, U-Net variants, Vision Transformers, diffusion-based or representation-learning models.
Define appropriate evaluation strategies and ensure analytical rigor, reproducibility, and scientific credibility.
Integrate imaging data with clinical, molecular, or spatial-omics data where relevant.
Balance innovation with practicality, ensuring solutions are scalable, interpretable, and fit-for-purpose.
Cross-Functional Collaboration Work closely with pathologists, radiologists, clinicians, and translational scientists to translate scientific questions into computational imaging solutions.
Clearly communicate modeling approaches, assumptions, results, and limitations to technical and non-technical stakeholders.
Contribute to shaping project-level research questions and study designs involving imaging data.
Support external collaborations through technical input and scientific exchange as needed.
Scientific Contribution & Mentorship Contribute to the organization’s scientific visibility through publications, presentations, and internal knowledge sharing.
Provide informal mentorship and technical guidance to junior scientists and collaborators.
Stay current with advances in AI, computer vision, and medical imaging to continuously elevate technical approaches.

Benefits

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible.

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