Principal AIOps Engineer

We are seeking a Sr. MLOps Engineer with a strong background in Data Engineering and a passion for building scalable AI/ML solutions. You will design, develop, and maintain ML pipelines and data platforms, ensuring reproducible, scalable, and secure AI deployments in R&D. This role is ideal for candidates who want to apply DevOps practices to AI/ML applications in the healthcare sector.

Key Responsibilities:

• Design, build, and maintain scalable MLOps pipelines for AI/ML applications.
• Apply software engineering best practices for managing large datasets across Data/ML platforms.
• Develop, deploy, and monitor ML models using MLOps tools such as AWS SageMaker, MLflow, TensorFlow, and PyTorch.
• Implement CI/CD pipelines using Terraform, CloudFormation, Git, Docker/Kubernetes, ECS/EKS, and Helm Charts.
• Build and maintain data pipelines and workflows leveraging AWS Data Lake technologies: Python, Apache Spark, AWS Lambda, Step Functions, Glue ETL, SQL.
• Collaborate with Data Scientists and Engineers to ensure reproducible and efficient model deployment.
• Balance development and research work to explore and integrate the latest trends in GenAI operations.
• Ensure compliance with organizational standards and best practices for data security and model governance.

Key Requirements / Minimum Qualifications:

• Master's or Ph.D. in Computer Science, Data Science, or related quantitative fields.
• 5+ years of hands-on experience in MLOps engineering and Data/AI platforms, preferably in medical devices or equivalent industry experience.
• Strong software engineering skills applied to Data/ML workflows.
• Hands-on experience with AWS SageMaker, MLFlow, TensorFlow, PyTorch.
• Experience in CI/CD, Infrastructure-as-Code (Terraform, CloudFormation), containerization (Docker/Kubernetes), and orchestration (ECS/EKS, Helm).
• Hands-on expertise with data lakes and ETL pipelines: Python, Spark, SQL, AWS Glue, Lambda, Step Functions.
• Working knowledge of cloud platforms and infrastructure (AWS preferred).
• Programming and scripting proficiency in Python; familiarity with CLI/SDK/CDK.
• AWS certifications in ML/Data preferred.
• Excellent communication skills in English (written and spoken).