Source description
About the role
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
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