Position Summary:

We are seeking a motivated Data Scientist to research, develop, and enhance machine learning and deep learning algorithms that drive innovative healthcare solutions. This role involves maintaining high data quality standards, collaborating with clinical and business partners to understand their needs, and translating advanced research into practical applications. The ideal candidate will assist in building and improving deep learning frameworks, manage projects independently, and work effectively both individually and within cross-functional teams. Staying current with emerging technologies and demonstrating strong communication, attention to detail, and persistence are essential for success in this role.

Essential Duties and Responsibilities:

Research, develop, and enhance machine learning and deep learning algorithms and frameworks for computer vision applications, translating cutting-edge research into practical healthcare solutions.
Implement and optimize deployment pipelines for trained models to enable efficient, scalable, and hardware-optimized inference.
Apply model optimization techniques to reduce computational overhead while preserving accuracy.
Maintain data quality and integrity across the data lifecycle to support robust algorithm development and model training.
Collaborate with clinical partners and internal stakeholders to understand needs and deliver AI solutions that improve model performance.
Assist in writing deep learning framework templates, identifying improvement areas, and implementing new model architectures.
Manage projects independently and contribute effectively as part of a team, ensuring reproducible analyses, clear documentation, and knowledge sharing.
Stay updated with the latest data science methods, technologies, and industry trends.
Demonstrate strong communication skills, persistence, attention to detail, and a drive to complete research projects end-to-end.

Qualifications:

M.S. or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics or related field.

Knowledge, Skills, and Abilities:

Strong foundation in state-of-the-art deep learning architectures (e.g., vision transformers) for computer vision tasks including image classification, object detection, and semantic segmentation.
Proficiency in deep learning libraries and frameworks, including PyTorch and TensorFlow.
Proficiency in C++ regarding object-oriented programming, data structure and performance optimization technique.
Solid knowledge of model optimization techniques, such as pruning, quantization, mixed-precision inference, and other performance-enhancing strategies.
Solid knowledge of model deployment tools, including ONNX, LibTorch, and TensorRT.
Strong grasp of model evaluation metrics, benchmarking, and best practices for computer vision model validation.
Self-driven with the ability to deliver on ambiguous projects with incomplete data.
Excellent written communication skills, especially in writing technical manuscripts.

Bonus:

Experience and knowledge in healthcare domain with successful outcomes.
Experience with CUDA programming for developing custom GPU kernels, optimizing computational performance, and accelerating deep learning workflows.

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