Manager, Machine Learning Engineering & Data Science, Hyderabad

• Own end-to-end delivery: Accountable for delivering ML/DS initiatives from problem definition through production, ensuring timelines, quality, and business impact are consistently met.
• Own ML platform and lifecycle capabilities: Build and evolve core systems for ML pipelines, experimentation, model versioning/promotion, deployment, and observability, ensuring reproducibility, governance, and production reliability.
• Be a hands-on technical leader: Stay close to the work, review designs, guide modeling approaches, participate in key technical decisions, and help unblock complex ML and data challenges.
• Partner deeply with product and stakeholders: Work closely with Product, Engineering, and business teams to shape problem statements, prioritize work, and ensure ML solutions align to clear outcomes and KPIs.
• Drive execution with operational excellence: Establish strong planning, tracking, and risk management practices; ensure ML systems are production-ready with robust pipelines, automated deployment workflows, and end-to-end monitoring/observability.

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