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