Machine Learning Engineer

Description :

We are looking for a curious and passionate Machine Learning Engineer to join our high-impact team. Youll work directly on ML models that analyze cardiac data, helping doctors save lives.

This role offers the unique opportunity to see your work make a tangible difference in patient outcomes while building state-of-the-art ML infrastructure.

What Youll Do :

• Design and Implement ML Models : Develop, train, and evaluate machine learning and deep learning models for cardiac datasets and associated metadata.
• Data Pipeline Development : Work with large, complex, and sometimes messy clinical datasets. Contribute to building robust and scalable data pipelines for data ingestion, cleaning, feature engineering, and labeling.
• Model Deployment and MLOps : Deploy models to production environments and monitor their performance in real-world clinical settings.
• Build and maintain REST APIs for model inference using frameworks like FastAPI or Flask. Design scalable API endpoints with proper request validation, error handling, and authentication.
• Implement and maintain robust MLOps practices, including version control, continuous integration / continuous deployment (CI / CD), and model monitoring in a production environment (e.g., cloud platforms like AWS, Azure, or GCP).
• Performance Optimization : Optimize model performance for inference speed and resource efficiency, crucial for deployment on various platforms (cloud, edge devices).
• Collaboration : Work collaboratively with software engineers, data scientists, and clinical domain experts to translate clinical needs into technical requirements and deliver high-impact solutions.
• Documentation and Research : Maintain detailed documentation of models, code, and experiments. Stay current with the latest research in deep learning, medical image analysis, and time-series analysis.
• Regulatory and Compliance : Develop documentation in order to comply with regulatory requirements such as CDSCO, FDA etc.

Required :

Preferred Skills :

(ref : hirist.tech)