Senior Engineer

RESPONSIBILITIES :

• As MLOps Engineer, you will work collaboratively with Data Scientists and Data engineers to deploy and operate advanced analytics machine learning models. You ll help automate and streamline Model development and Model operations. You ll build and maintain tools for deployment, monitoring, and operations. You ll also troubleshoot and resolve issues in development, testing, and production environments.
• Enable Model tracking, model experimentation, Model automation Develop scalable ML pipelines
• Develop MLOps components in Machine learning development life cycle using Model Repository (either of) : MLFlow, Kubeflow Model Registry
• Machine Learning Services (either of) : Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS / SaaS
• Work across all phases of Model development life cycle to build MLOPS components
• Build the knowledge base required to deliver increasingly complex MLOPS projects on the Cloud(AWS, Azure, GCP) / On Prem Be an integral part of client business development and delivery engagements across multiple domains.

QUALIFICATIONS : REQUIRED QUALIFICATIONS :

EDUCATION :

Skills Required

Java, C#, Machine Learning, MLops, C++, Docker, Pyspark, Python