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Spectral AI · 2 days ago

Data Scientist

United States

Full-time

Remote

Mid Level

Spectral AI is seeking a motivated Data Scientist to research, develop, and enhance machine learning and deep learning algorithms for innovative healthcare solutions. The role involves maintaining high data quality standards and collaborating with clinical and business partners to translate research into practical applications.

AnalyticsArtificial Intelligence (AI)BiotechnologyHealth CareMachine LearningMedical Device

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

Qualification

Deep learning architecturesPyTorchTensorFlowModel optimization techniquesC++ programmingModel deployment toolsModel evaluation metricsHealthcare domain experienceCUDA programmingWritten communicationSelf-driven

Required

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

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