Senior Machine Learning Engineer (Consumer Team), Hyderabad

, and we are an early, enthusiastic adopter of agentic AI development workflows.

What You'll Do

Technical Leadership & Architecture

• Design and operate low latency online serving systems for fraud scoring, message decisioning and real-time personalization
• Build ML models for identity resolution, audience intelligence, content affinity modeling, genre-preference modeling and time-series forecasting across global markets
• Integrate with personalization systems to consume in-app user signals
• Design feature pipelines that fuse real-time streaming signals with batch-computed features for online scoring
• Partner with Product, Engineering, and Data Science to translate business problems into well-scoped ML solutions
• Evaluate new technologies and approaches, including DCR-native modeling, graph ML, agentic ML orchestration, and LLM-augmented pipelines, with clear build/buy/partner recommendations.

Production ML Systems

systems that connect unauthenticated device IDs and first-party cookies to households/persons with calibrated confidence across WBD brands.

• Lead the evolution of

, including ML Promo Optimizer, STAT v2, lookalike modeling inside Snowflake DCR, and content segmentation.

• Own ML architecture for

use cases such as audience growth, demand, yield, and pricing, ensuring models are monitored and continuously improved.

• Bring ML personalization signals, such as genre/content affinity and engagement trends, into batch and future real-time activation paths.

Experimentation, Quality & Observability

• Design offline and online evaluation approaches with clear baselines, success metrics, experiment design, and promotion criteria.
• Improve feature and label quality, leakage prevention, bias checks, calibration, explainability where applicable, and impact measurement.
• Identify technical risks early, document tradeoffs, and drive mitigation plans with engineering, data, product, and business partners.
• Turn incidents and postmortems into reusable standards, automated checks, and platform improvements.

Cross-functional Partnership & Mentorship

• Mentor MLE 2 engineers through architecture reviews, design discussions, implementation guidance, and hands-on problem solving.
• Partner with the ML leads on technical roadmap shaping, execution planning, capability development, and technical input into hiring profiles.
• Represent the Hyderabad team in technical forums with ML, Data Engineering, Product, Ad Sales, and US-based stakeholders.
• Create clear design docs, architecture reviews, readiness reviews, and postmortems that strengthen engineering culture.

What You'll Bring:

• 5 - 8 years of ML engineering experience, or 2+ years with a Ph.D., with demonstrated Senior-level scope, technical ownership, and cross-team impact.
• You are comfortable owning systems end-to-end, from problem definition through serving and monitoring, not just the modeling layer.
• You have worked on optimization problems like ranking, personalization, or multi-objective decisioning in environments with interacting metrics.
• You have hands on experience with Databricks, Spark and Sagemaker.
• Experience architecting production ML systems for large user populations, with a track record of setting standards and influencing across teams.
• Expert proficiency with ML frameworks (PyTorch, TensorFlow, XGBoost/LightGBM, scikit-learn) and deep understanding of statistics and ML fundamentals.
• Master's or Ph.D. in Computer Science, Statistics, Machine Learning, or a related field (or equivalent industry experience).
• Excellent communication skills, with the ability to explain technical solutions to engineering, science, product, and executive audiences.

Preferred

• Streaming / Identity / Fraud / Ad-tech ML: identity resolution, audience modeling, recommendation/ranking, content understanding.

Hands-on experience with agentic AI frameworks at production scale

• Experience with real-time feature serving and low-latency inference, and with mixture-of-experts or graph neural networks.
• Published research or conference presentations in relevant ML domains.

Our Technology Stack

• Primary platform: AWS , Databricks
• Warehouse: Snowflake
• Activation: Mosaic, FreeWheel, Google Ad Manager.
• Languages: Python (primary), SQL, Scala (as needed).

• A Great Place to work
• Equal opportunity employer
• Fast track growth opportunities

How We Get Things Done...

This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.

Championing Inclusion at WBD

Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.

If you're a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.