ML Engineer

We are looking for a Machine Learning Engineer with strong expertise in designing, building, automating, and deploying end-to-end ML workflows on AWS. The ideal candidate will have deep experience in operationalising ML solutions, implementing robust CI/CD practices, and ensuring high-quality, production-grade ML pipelines.

Requirements

• Strong expertise in designing, building, automating, and deploying end-to-end ML workflows on AWS
• Proven experience in designing, developing, and deploying SageMaker Pipelines
• Ability to operationalise ML pipelines through the full development lifecycle
• Experience writing and maintaining unit tests, integration tests, and pipeline validation tests for ML workflows and SageMaker components
• Strong experience automating ML operations using Airflow DAGs
• Extensive experience with GitLab in enterprise environments
• Proficient in Python, PySpark, and SQL for developing robust ML pipelines
• Deep understanding and hands-on experience with AWS services including S3, KMS, Lambda, Secrets Manager, CodeBuild, CodePipeline, SageMaker Pipelines, and SageMaker Endpoints
• Experience managing secure, scalable cloud environments following enterprise security standards
• Hands on experience in orchestrating complex workflows using Airflow and integrating real-time streaming data from Kafka