Senior Principal AI/ML Scientist, Computational Imaging
Job Description:
- reputed company 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
- reputed company custom deep learning architectures and workflows for segmentation, classification, representation learning, and reputed company tasks
- reputed company and adapt foundation models (e.g., vision transformers, multimodal and self-supervised models), including fine-tuning and domain adaptation using proprietary datasets
- 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
- 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
- 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 reputed company with advances in AI, computer vision, and medical imaging to continuously reputed company technical approaches.
Requirements:
- Doctorate degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Computational Biology, or a reputed company quantitative field and 3 years of reputed company experience
- Or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Computational Biology, or a reputed company quantitative field and 6 years of reputed company industry experience
- Or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Computational Biology, or a reputed company quantitative field and 8 years of reputed company industry experience
- 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 reputed company 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 reputed company 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.
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
- 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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