Job Summary: Design, develop, and deploy AI/ML models and intelligent systems that enhance clinical decision-making, operational efficiency, and patient outcomes. Collaborate with cross-functional teams to integrate AI capabilities into scalable, secure, and compliant SaaS platforms. Key Responsibilities: Machine Learning & Deep Learning Expertise in supervised, unsupervised, and reinforcement learning Familiarity with CNNs, RNNs, transformers, and generative models Proficiency in TensorFlow, PyTorch, Scikit-learn Programming & Software Engineering Advanced skills in Python, R, SQL; optionally Java or Scala Experience with CI/CD, Docker, Kubernetes, GitOps Data Engineering & Architecture Building scalable data pipelines and real-time analytics Experience with Spark, Hadoop, and cloud-native platforms (Azure, AWS, GCP) Healthcare Compliance & Interoperability Knowledge of HIPAA, HL7, FHIR standards Experience integrating AI into EHRs and clinical workflows AI Strategy & Responsible Use Ethical AI design, bias mitigation, and explainability Ability to align AI initiatives with business and clinical goals Required Qualifications: Education & Experience Bachelor’s or Master’s degree in Computer Science, Data Science, or related field. 6+ years of experience in AI/ML engineering, preferably within healthcare SaaS environments Proven track record of deploying models in production and integrating with cloud-native platforms Other Preferred Knowledge, Skills, Abilities or Certifications: Cloud & AI Certifications Healthcare Standards & Compliance Ethical AI & Responsible Use Data Engineering & Real-Time Analytics