Role Overview
We’re looking for an AI Engineer with strong Python expertise to help design and deliver intelligent, scalable AI solutions across our healthcare systems. You'll work with cross-functional teams to develop ML models, implement data pipelines, and contribute to the deployment and monitoring of AI-powered features.
Key Responsibilities
- Develop machine learning and deep learning models in Python using frameworks like TensorFlow or PyTorch.
- Write modular, testable, and production-ready Python code for data preprocessing, feature engineering, and model training.
- Build and maintain scalable Python-based data pipelines using tools like Airflow and Pandas.
- Deploy AI models in production using Python microservices and container technologies (e.g., Docker, FastAPI, Flask).
- Collaborate with MLOps engineers to automate CI/CD pipelines for model training, testing, and deployment.
- Implement monitoring, logging, and model performance tracking using Python tools and libraries.
- Collaborate with data scientists to interpret data and ensure clinical relevance of AI solutions.
- Adhere to software development best practices, version control (e.g., Git), and regulatory and quality standards.
Required Qualifications
- MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- 3+ years of professional experience in AI/ML development using Python.
- Strong knowledge of the Python ecosystem for machine learning (e.g., TensorFlow, PyTorch, Pandas, NumPy, FastAPI).
- Experience deploying Python-based ML models in production environments (on cloud platforms like Azure or AWS).
- Familiar with MLOps concepts, data versioning (DVC), and model lifecycle management using tools like MLflow or Weights & Biases.
- Understanding of software testing in Python (e.g., pytest) and experience with performance optimization.
