Manager - Data Sciences

Client Interview ExpectationsJob Description ML Engineer Job Summary Were looking for a Machine Learning Engineer who is experienced in deploying and managing machine learning models at scale in production for our ML Operations team The team is a cross functional team and has Software Engineers and DS Engineers and closely works with data scientists and data engineers in operationalizing ML models Roles and Responsibilities As an ML Engineer in the MLOps team you will be a key stakeholder and owning responsibility in operationalize and monitor machine learning models using high end tools and technologies Data Science quality assurance and testing Monitoring and troubleshooting of in production ML models and tools Build and maintain production level python libraries Execute best practices in version control and continuous integration delivery Collaborate with data scientists engineers and other key stakeholders Work well in a fast paced cross functional environment Skills Requirements Experience in implementing machine learning life cycle on AWS or other cloud platforms Knowledge on Docker Jenkins Kubernetes and other DevOps tools Familiarity with Kubeflow or mlflow Experience in Python Experience with Machine learning frameworks libraries and agile environments Experience with version control tools such as Git Bitbucket etc Experience with SQL and databases Outstanding analytical and problem solving skills