MLOps Engineer

We are looking for an experienced MLOps Engineer to build and maintain a secure, scalable deployment platform for the PDx Model. The role involves automating ML release pipelines, implementing governance and monitoring, and providing production support for the PDx Lead Scoring Model.

Responsibilities:

• Build and maintain secure ML deployment platforms using AWS SageMaker and related AWS services.
• Develop automated CI/CD pipelines for ML model training, testing, and deployment.
• Automate build and release processes for training and inference pipelines.
• Implement model registry, versioning, experiment tracking, and lifecycle management.
• Use Docker for containerization and support reliable ML deployments.
• Monitor production systems using AWS CloudWatch and observability tools.
• Implement security controls, access management, governance, and model lineage.
• Troubleshoot production issues and ensure reliable operation of deployed ML models.
• Collaborate with Data Scientists and engineering teams to transition ML models into production.
• Maintain Python codebases and Git repositories while improving deployment automation.

Requirements:

• 4-7 years of engineering experience with hands-on production AI/ML deployments.
• Strong practical experience with AWS SageMaker and ML deployment pipelines.
• Proven experience in CI/CD automation and production ML operations.
• Strong troubleshooting, ownership, and problem-solving skills.
• Experience working in enterprise cloud environments.
• Excellent communication and stakeholder collaboration skills.
• Immediate joiners preferred.

Key Skills:

• AWS SageMaker and AWS ML Ecosystem
• MLOps and Machine Learning Deployment
• CI/CD Pipeline Automation
• Python and Git
• Docker and Containerization
• ML Training and Inference Pipelines
• Model Registry, Versioning and Experiment Tracking
• AWS CloudWatch and Observability
• Security, Access Control and Model Lineage
• Production Support and Troubleshooting

Skills

CI / CD, CloudWatch, Docker, Git, MLOps, Python, SageMaker