Job Description

We’re 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.