Proactively develop, maintain and evangelize technical knowledge in Machine Learning and adjacent technologies. Establish development and delivery best practices for ML implementations to minimize rework and maintenance cost. Deliver efficiency based on measurable metrics of scale, speed, model performance, stability of environment and cost reduction

• Engage with data scientists and business leads to identify the inventory of AI/ML models that have can be scaled up.
• Work along with platform engineers and data architects and make the right decision of architecture and design for industrialization of models
• Ownership of complete module that includes design, development, solutioning and testing of AI/ML module as per requirements while collaborating with respective customers
• Work as an effective teammate, providing training and support to peers and team members in a collaborative manner in the specific areas of specialization.
• Design and develop ML pipelines for data pre-processing, model training, model evaluation and model monitoring.
• Strong working knowledge in ML workflows and CI/CD practices to ensure smooth model deployment and retraining
• Collaborate with DevOps and IT teams to deploy ML models into production environments, ensuring scalability and security
• Responsible for defining our standard processes, and enabling the Data Scientists we partner with by providing guidance and mentoring on the application of these practices to our work

• B.Tech, M.Tech from a top Tier University
• Minimum 9 years of relevant experience in data Science, advanced analytics and product development. Cross-industry experience highly preferred.
• Minimum 5 years of experience in ML ops and ML engineering roles in large scale programs. Key competencies – Advanced knowledge of multi cloud environments such as AWS, MS Azure, Databricks along with understanding and familiarity with software development principles