Senior Manager, Machine Learning Engineering (Data & Audience Platform), Hyderabad

Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team in Hyderabad builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery directly driving advertising yield, marketing efficiency, engagement, and retention.

At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure feature stores, training and serving pipelines, and MLOps that makes our work reliable, repeatable, and scalable. We build primarily on Databricks, with strong working knowledge of Snowflake and AWS, and we are an early, enthusiastic adopter of agentic AI development workflows.

About the Role

This is the most critical hire for WBD's Hyderabad ML Engineering build-out. As Senior ML Engineering Manager, you will establish, lead, and grow the Hyderabad ML Engineering center of excellence a team of seven individual contributors spanning identity intelligence, audience intelligence, content affinity modeling, forecasting, and ML platform engineering. You will be the single accountable leader for the team's technical execution, people development, and cross-functional delivery in India, operating as a true extension of the Director of Engineering. All of the Hyderabad ML/DS individual contributors report to you, and you report into the Director.

This role demands an exceptional blend of technical depth (you must credibly engage in Staff-level ML architecture discussions), people leadership (you will manage a diverse IC ladder from MLE 2 to Staff), and organizational influence (you will represent Hyderabad across WBD's global data, product,



and advertising organizations). You are not just a manager you are a builder, a technical partner, and a culture carrier.

What You'll Do

Team Leadership & People Development

- Directly manage 7 ICs (2 MLE 2, 3 Senior MLE, 1 Staff MLE, 1 Staff DS); own their performance, growth, and career development.
- Establish a high-performance engineering culture: technical excellence, ownership, psychological safety, rigorous experimentation, and continuous learning.
- Define clear role expectations, growth paths, and promotion criteria aligned with WBD s global ML engineering job family; conduct regular 1:1s, performance reviews, and career conversations, addressing performance gaps proactively.
- Lead hiring for the Hyderabad team: define the hiring bar, design interview processes, attract top ML talent, and build a strong, diverse local pipeline.
- Foster an inclusive, collaborative environment that bridges India and US time zones effectively.

Technical Leadership & Oversight

- Maintain sufficient technical depth to review ML architecture proposals, challenge design decisions, and unblock technical escalations across all workstreams.
- Partner with the Staff MLE to set and enforce technical standards: MLOps practices, code quality, model-evaluation rigor, and documentation.
- Own the technical roadmap for the team s ML systems identity intelligence, audience intelligence, content affinity, forecasting in alignment with global ML strategy.
- Drive adoption of the team s core stack: Databricks (primary), AWS SageMaker, Snowflake, MLflow, and agentic AI tooling (Cursor, Copilot, Amazon Q, Databricks Genie, Snowflake Cortex,



MCP).
- Ensure production ML systems are reliable, monitored, cost-effective, and continuously improved; own the team s on-call and incident-response posture.

Program Execution & Delivery

- Own end-to-end delivery accountability for Hyderabad s ML projects: scope, milestones, dependencies, risks, and stakeholder communication.
- Run effective agile processes adapted to ML realities (research uncertainty, data dependencies, experiment iteration), with D90 planning rhythms and quarterly OKR alignment.
- Proactively identify and resolve cross-team dependencies with Data Engineering, Product, Ad Sales, and Legal/Privacy.
- Maintain a clear view of capacity, prioritization trade-offs, and commitments; communicate status and risks transparently to the Director.

Key ML Workstream Ownership

- Identity Intelligence: oversee delivery of the probabilistic ID spine resolving unauthenticated signals (device IDs, 1P cookies) to households/persons with calibrated confidence across all WBD brands.
- Audience Intelligence: oversee ML Promo Optimizer, STAT v2 (single-title affinity retrieval), lookalike modeling (LAL 2.0+ in Snowflake DCR), and segmentation that power advertising and marketing activation.
- Content Affinity & Personalization: oversee genre-preference and content-affinity models and engagement-based personalization signals feeding HBO Max and CNN surfaces.
- Forecasting: oversee ML-based audience, engagement, and yield/revenue forecasting supporting Finance, Content, and Marketing planning.
- MLOps Platform: ensure the team s feature store, training/serving pipelines, model registry, and monitoring are production-grade, well-documented, and consistently adopted.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Manager, ML Eng (Data & Audience Platform) (Hyderabad)
🏢 Warner Bros. Discovery
📍 Hyderabad