Computer Vision Scientist

• 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., Lead development, training, deployment, and optimization of deep learning computer vision models using aerial and geospatial imagery. Build high-quality datasets, collaborate with product and engineering teams to translate requirements, and mentor data science team members while establishing best practices for production ML. Top Skills: AWSBigQueryClaude CodeCursorDockerGitGoogle Cloud Platform (Gcp)KubernetesMatplotlibOpencvPillowPlotlyPythonPyTorchSQLTensorFlow Block

• 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.

Lead the development and deployment of production-ready computer vision and deep learning systems for medical imaging. Responsibilities include model development, end-to-end ML pipelines, validation, data strategy, clinical readiness, explainability, regulatory support, cross-functional collaboration, and technical mentorship. The role requires translating research into reliable, clinically validated AI solutions for real-world healthcare environments. The summary above was generated by AI

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Sora Union is a globally distributed professional services company that specializes in Design, Software Engineering. Our experienced talent comes from communities where there is displacement or risk of displacement due to conflict or climate change. We provide services to global companies and start-ups across various industries, including healthcare, financial services, technology, and education.