AI Model Deployment Engineer

Job Title : MLOps Engineer Experience : Minimum 3 Years

Location : Chennai

Employment Type : Full-time

About the Role :

We are seeking an experienced MLOps Engineer with a focus on healthcare AI to join our innovative team. This role involves designing, implementing, and maintaining scalable MLOps pipelines for deploying deep learning models, including very deep vision models and large language models (LLMs), in clinical research, diagnostics, and healthcare analytics. The ideal candidate will have hands-on experience in healthcare AI environments, ensuring reliable, efficient, and compliant model deployments.

Key Responsibility :

• Design and implement CI / CD pipelines for machine learning models using tools like Jenkins, GitHub Actions, or GitLab CI.
• Deploy and manage very deep vision models (e.G., CNNs for medical imaging) and LLMs (e.G., for NLP in clinical notes) in production environments using Docker, Kubernetes, and cloud platforms (e.G., AWS, Azure, GCP).
• Develop monitoring, logging, and alerting systems for ML models to ensure performance, drift detection, and retraining triggers using tools like Prometheus, Grafana, or MLflow.
• Collaborate with data scientists, AI engineers, and clinicians to integrate models into healthcare workflows, handling large-scale medical datasets.
• Implement version control for models and data using tools like DVC, MLflow, or Kubeflow.
• Ensure compliance with healthcare regulations (e.G., HIPAA, GDPR) through secure data handling, model auditing, and privacy-preserving techniques.
• Optimize model inference for efficiency, including model quantization, serving with TensorFlow Serving, TorchServe, or BentoML.
• Troubleshoot deployment issues and perform A / B testing for model iterations.
• Automate infrastructure as code using Terraform or Ansible for reproducible environments.

Must-Have Skills & Experience