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).

Principal AIOps Engineer