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.