AI/ML Lead – Healthcare Domain

Job Title: AI/ML Lead – Healthcare Domain
Location: Remote
Experience: 10+ Years (including 3+ years in a leadership role)
Employment Type: Full-Time / Contract

Job Summary:

We are seeking an experienced AI/ML Lead with deep expertise in designing, developing, and deploying machine learning solutions within the healthcare domain. The ideal candidate will have a strong background in data science, applied machine learning, and AI engineering, with proven experience translating clinical or healthcare business needs into scalable ML/AI models. This role requires technical leadership, strategic thinking, and the ability to work with cross-functional teams to drive outcomes in regulated environments.

Key Responsibilities:

• Lead the end-to-end development of AI/ML models focused on healthcare use cases such as clinical decision support, predictive analytics, patient stratification, and medical imaging.
• Collaborate with data engineers, clinicians, and product teams to understand requirements and define AI strategies aligned with business and regulatory needs.
• Architect and build scalable ML pipelines using modern frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Evaluate and apply techniques such as NLP, deep learning, computer vision, and time-series analysis on structured and unstructured healthcare data (EHR, claims, imaging, genomics).
• Ensure model interpretability, fairness, and compliance with HIPAA and healthcare data governance policies.
• Optimize models for performance, reliability, and production-readiness, including containerization and CI/CD for ML.
• Mentor junior data scientists and machine learning engineers; promote best practices in research, experimentation, and deployment.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Biomedical Engineering, or related field (PhD preferred).
• 8–10+ years of experience in data science/ML, with at least 3 years in a leadership role.
• Strong programming skills in Python and experience with ML libraries: TensorFlow, PyTorch, Scikit-learn, etc.
• Deep understanding of AI/ML fundamentals including model evaluation, tuning, and statistical techniques.
• Proven experience applying ML/AI in healthcare domains such as provider analytics, medical coding, population health, or remote monitoring.
• Familiarity with healthcare data standards (e.g., HL7, FHIR, ICD-10, CPT) and privacy regulations (e.g., HIPAA).
• Experience deploying models in cloud environments such as AWS, Azure, or GCP.
• Excellent communication and stakeholder management skills.