Sr Computer Vision Scientist
Sora Union · Remote · remote · Posted 37d ago
Undisclosed7–12 yrsfulltimeSourced from
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About this role
We re looking for a Senior Computer Vision Scientist who will lead the development and deployment of production-ready computer vision and AI solutions for medical imaging, translating state-of-the-art machine learning research into robust, clinically validated systems that can operate reliably in real-world healthcare environments and directly support patient care.
Youll be responsible for:
- Develop Medical Imaging AI - Build and optimize computer vision and deep learning models for medical imaging and multimodal datasets.
- Own the End-to-End AI Pipeline - Lead ML development from data preprocessing and training through inference, optimization, and production deployment.
- Drive Model Validation - Design evaluation frameworks and ensure models meet clinical performance, reliability, and generalization standards.
- Drive Data Strategy - Define data curation, annotation, and quality processes while addressing bias, noise, and dataset imbalance.
- Support Clinical Readiness - Contribute to validation, documentation, explainability, and regulatory requirements for clinical AI.
- Collaborate Cross-Functionally - Partner with clinicians, engineers, and product leaders to translate clinical needs into scalable AI solutions.
- Provide Technical Leadership - Mentor team members, shape AI architecture and roadmap, and bring impactful advances in medical AI into production.
Ideally, youll have:
- 7+ years of experience in computer vision, deep learning, machine learning, or a closely related field, with significant hands-on experience building real-world AI systems.
- Strong expertise in deep learning frameworks such as: PyTorch, TensorFlow
- Solid understanding of medical imaging standards and formats, including DICOM and NIfTI.
- Experience working with large, noisy, and imperfect real-world datasets.
- Strong programming skills in Python; familiarity with C++ is a plus.
- Strong expertise in computer vision and deep learning, with practical experience using architectures such as CNNs, Vision Transformers, and/or self-supervised learning.
- Experience developing AI-enabled medical devices or FDA-regulated medical software.
- Familiarity with model interpretability, uncertainty estimation, and calibration in clinical AI systems.
- Proven experience working with medical imaging or other highly complex, heterogeneous datasets; experience with MRI, CT, ultrasound, pathology, or multimodal data is highly desirable.
- Demonstrated ability to take ML models from research/prototype through validation and into production.
- Strong understanding of model evaluation, validation, generalization, uncertainty, calibration, and clinical performance metrics.
- Experience designing or contributing to data curation, annotation, quality control, and dataset management processes.
- Strong software engineering skills and experience building scalable ML/inference pipelines and production systems.
- Experience working cross-functionally with clinicians, engineers, and product teams.
- Understanding of clinical AI validation, explainability, documentation, and regulatory requirements is a strong advantage.
- Strong problem-solving and scientific thinking, with the ability to translate ambiguous clinical problems into practical ML solutions.
- Demonstrated technical leadership, including mentoring, influencing technical direction, and driving projects from concept to deployment.
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
Data StrategyDICOMComputer Visionmedical imagingdata preprocessingdataset managementdeploymentDevelopment And DeploymentHealthcareMedical DevicesArchitectureDeep LearningFinancial ServicesAi SolutionsArtificial IntelligenceMachine Learning