Deep Learning Data Scientist II

Spectral MD Inc is hiring a Deep Learning Data Scientist II to support research and development of AI and ML algorithms for computer vision in healthcare. This onsite role in Dallas, TX focuses on building deep learning models, preserving data quality, and improving performance for efficient deployment, while partnering with clinical and internal stakeholders to deliver practical solutions.

What you’ll work on

• Research, develop, evaluate, and enhance machine learning and deep learning algorithms for computer vision, turning AI research progress into healthcare-ready capabilities.
• Build and optimize model deployment pipelines to support efficient, scalable, hardware-optimized inference.
• Apply model optimization techniques to improve computational efficiency and inference performance while maintaining accuracy.
• Maintain data quality and integrity across the data lifecycle to enable robust algorithm development, training, and evaluation.
• Collaborate with clinical partners and internal stakeholders to translate clinical and business needs into appropriate AI/ML solutions.
• Independently manage assigned R&D projects from problem formulation through implementation, evaluation, and delivery.
• Ensure reproducibility using clear documentation, version-controlled workflows, and effective knowledge sharing.
• Stay current with advances in AI/ML and computer vision, evaluating applicability to ongoing R&D.
• Communicate technical methods, results, and recommendations to both technical and non-technical audiences.

Key qualifications

• M.S. or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or a related quantitative field.
• Minimum two years of relevant research or professional experience in computer vision.
• If holding a master’s degree, required experience must be professional experience gained after completion of the degree.
• Strong Python programming skills and experience building maintainable, reproducible ML code.
• Strong foundation in modern deep learning architectures, including vision transformers, for image classification, object detection, and semantic segmentation.
• Proficiency with deep learning frameworks and libraries, including PyTorch and TensorFlow.
• Strong understanding of AI/ML evaluation metrics, benchmarking methodologies, and best practices for rigorous computer vision model validation.
• Solid understanding of model optimization techniques such as pruning, quantization, and mixed-precision inference to improve efficiency and inference performance.
• Working knowledge of deployment and inference tools including ONNX, LibTorch, and TensorRT.
• Self-driven ability to navigate ambiguous research problems with incomplete data and still deliver high-quality results.
• Strong written and verbal communication skills, including preparation of technical documentation, reports, and scientific manuscripts.

Preferred qualifications

• Experience with multispectral and/or hyperspectral imaging data.
• Experience with generative AI models for medical image synthesis and simulation.
• Experience applying AI/ML methodologies to healthcare or biomedical applications, with demonstrated contributions to successful research, clinical, or product outcomes.

Technologies you’ll use

• Python, PyTorch, TensorFlow
• ONNX, LibTorch, TensorRT

Work setup

• Location: Dallas, TX (onsite)
• Travel: N/A
• Physical requirements: Prolonged periods of sitting at a desk and working on a computer.