MLOps Engineer

Build and optimize scalable, secure, and cost-effective AWS-based infrastructure for ML/GenAI workloads

Develop automated workflows for data ingestion, model training, testing, deployment, and monitoring using tools like AWS SageMaker, Step Functions, and Lambda

Implement data quality checks, lineage tracking, and compliance standards for curated datasets

Integrate ML pipelines with DevOps practices, ensuring seamless collaboration between data science and engineering teams

Deploy monitoring solutions for model performance, drift detection, and system health using AWS CloudWatch and custom dashboards

Ensure adherence to security best practices and governance requirements for AI deployments

• Work closely with Data Scientists to operationalize models and optimize deployment strategies