AI Engineer

Overview

We are seeking a skilled AI/ML Engineer with 4–6 years of hands-on experience in designing and deploying machine learning models, preferably within the clinical or healthcare domain. The ideal candidate will bring a deep understanding of data science techniques, clinical data processing, and regulatory awareness to help build impactful AI-driven healthcare solutions.

Key Responsibilities

• Design, develop, and deploy ML/DL models tailored for clinical data applications (e.g., EHR, imaging, genomics).
• Preprocess and clean large, complex datasets, ensuring compliance with healthcare data standards (e.g., HL7, FHIR).
• Collaborate with clinical experts, data engineers, and product teams to understand and define ML problem statements.
• Evaluate model performance using appropriate statistical and domain-specific metrics.
• Implement pipelines for data ingestion, model training, and deployment in production environments (cloud/on-premise).
• Ensure AI/ML solutions adhere to privacy, security, and ethical standards (HIPAA, GDPR, etc.).
• Maintain thorough documentation and contribute to knowledge sharing within the team.
  
  

• Bachelor’s or Master’s degree in Computer Science, Biomedical Engineering, Data Science, or a related field.
• 4–6 years of experience in machine learning and data science roles.
• Strong proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn, etc.).
• Experience working with structured and unstructured clinical data.
• Familiarity with clinical terminologies (e.g., SNOMED CT, ICD-10) and healthcare interoperability standards.
• Experience with cloud platforms (AWS, GCP, or Azure) for ML model development and deployment.
  
  

• Prior experience in developing AI models for diagnosis, risk prediction, or clinical decision support.
• Knowledge of regulatory and ethical considerations in clinical AI systems.
• Publications, patents, or contributions to open-source healthcare AI projects.