Senior Engineer_ MLOPs

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:

• 5-10 years experience building production-quality software
• Strong experience in System Integration, Application Development or DataWarehouse projects across technologies used in the enterprise space
• Basic Knowledge of MLOps, machine learning and docker
• Object-oriented languages (e.g. Python, PySpark, Java, C#, C++ )
• Experience developing CI/CD components for production ready ML pipeline.
• Database programming using any flavors of SQL
• Knowledge of Git for Source code management
• Ability to collaborate effectively with highly technical resources in a fast-paced environment
• Ability to solve complex challenges/problems and rapidly deliver innovative solutions
• Team handling, problem solving, project management and communication skills creative thinking
• Foundational Knowledge of Cloud Computing either one AWS, Azure or GCP
• Hunger and passion for learning new skills