Head of Machine Learning Engineering

Company Description: HOPPR is pioneering the next frontier in healthcare technology with the development of a medical-grade platform for the creation and deployment of foundation models in medical imaging. Co-founded by Dr. Khan M. Siddiqui, a renowned leader in healthcare technology and AI, HOPPR is dedicated to improving patient care and outcomes through cutting-edge innovation. Our platform integrates deep learning, AI, and proprietary privacy-compliant trust architecture, setting new standards in healthcare. Role Description: HOPPR is seeking a Head of Machine Learning to manage our ML team in developing and deploying state-of-the-art multi-modal foundation models. As the Head of ML Engineering, you will be responsible for designing, developing, and optimizing these models and processes to fine-tune these models. You will lead a team of ML engineers and scientists, collaborate with data scientists and physicians, and drive the research and development of models through the development life-cycle. Your role will be critical in ensuring that HOPPRs models are not only high-performing but also robust, interpretable, and rigorously validated for clinical translation, meeting the highest standards of safety, compliance, and real-world reliability. Key Responsibilities: • Lead and mentor a team of ML engineers, fostering a culture of innovation and technical excellence. • Architect and optimize multi-modal deep learning models. • Oversee the end-to-end ML pipeline, including data preprocessing, model training, evaluation, and deployment. • Drive the integration of AI models into the HOPPR platform, ensuring seamless interoperability. • Collaborate with clinicians and regulatory teams to ensure AI models meet medical and compliance standards (e.g., FDA, HIPAA). • Optimize models for real-world performance, focusing on generalizability, robustness, and explainability. • Lead initiatives in model interpretability, bias mitigation, and continual learning. • Scale ML infrastructure and MLOps best practices for efficient model development and deployment. • Stay at the forefront of ML advancements and implement cutting-edge techniques in deep learning and medical imaging AI. • Work closely with cross-functional teams, including product, engineering, and regulatory teams, to align AI solutions with business goals. Qualifications: • 7+ years of experience in ML engineering, with at least 3+ years in a leadership role. • PhD or MS in Computer Science, Machine Learning, Biomedical Engineering, or a related field. • Extensive experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and medical imaging libraries (e.g., MONAI, DICOM, ITK). • Strong knowledge of CNNs, transformers, self-supervised learning, and other advanced deep learning architectures. • Experience with MLOps, cloud-based ML pipelines, and model deployment in production environments (AWS/GCP/Azure). Skills: • Understanding of regulatory requirements for AI in healthcare (FDA, CE, HIPAA, etc.). • Ability to work with large-scale medical imaging datasets and handle challenges such as data heterogeneity and label quality. • Strong leadership, mentorship, and team-building skills. • Passion for using AI to improve healthcare and a deep understanding of the challenges in medical imaging AI. Apply tot his job