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:

1. 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
2. Programming & Software Engineering
   • Advanced skills in Python, R, SQL; optionally Java or Scala
   • Experience with CI/CD, Docker, Kubernetes, GitOps
3. Data Engineering & Architecture
   • Building scalable data pipelines and real-time analytics
   • Experience with Spark, Hadoop, and cloud-native platforms (Azure, AWS, GCP)
4. Healthcare Compliance & Interoperability
   • Knowledge of HIPAA, HL7, FHIR standards
   • Experience integrating AI into EHRs and clinical workflows
5. 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