Description
We are seeking a skilled AI/ML Engineer with 46 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.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Biomedical Engineering, Data Science, or a related field.
- 46 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.
Preferred Qualifications
- 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.
