Data Engineer

Own delivery and execute AI/ML services at Production scale (for Personalization & Content squads) Lead design and development of robust ML services that are optimized for efficiency and performance in collaboration with data & tech teams Establish best practices for scalable, impactful solutions Influence tech team counterparts and drive alignment Work Experience & Skills: Role 1 (ML engineer - manager) 7+ years of hands-on experience working as an MLE/MLOps or Full-stack Engineer Strong software design & development experience in TypeScript with NodeJS Experience in building and scaling Machine Learning services (APIs) on AWS - API Gateway, Serverless Computing, Caching, Storage and Database concepts using AWS CDK. Familiarity with EKS is a plus. Strong in architecture, data structures & algorithms and familiarity with open-source AI/ML tools and frameworks (e.g. PyTorch, Keras, TensorFlow and TFServ) Experience working in scrum teams with Agile tools like Jira, Miro, Confluence, etc. In addition to the technical skills, all our team members are evaluated on organization-defined Capabilities, which for these roles are: Innovative: To design forward-thinking, scalable solutions aligned with business goals. Drives Results: To deliver tangible outcomes at speed while navigating complexity and ambiguity. Collaborates: To work seamlessly with data scientists, engineers, and tech counterparts, fostering strong partnerships. Inspiring Communication: To translate technical concepts into actionable strategies for both technical and non-technical stakeholders. Openness: To tackle challenges constructively, seek feedback, and create an environment of trust and collaboration Hands-on delivery also expected Role 2 (ML engineer - senior engineer) Expectations for the ML Engineer (3+ years of experience) would be similar from a tech stack point of view, but they will be more hands-on development / execution as opposed to design & strategy that the senior / lead would be involved in.