Senior Machine Learning Engineer, Hyderabad

For more information, please visit www.wbd.com.

Meet our Team

Warner Bros. Discovery (WBD) brings together iconic entertainment, news, and sports brands including HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, and Food Network. Within the SPARK organization, our Hyderabad Machine Learning Engineering team turns first-party audience signals into ML capabilities for identity, audience intelligence, advertising, personalization, forecasting, 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

Warner Bros. Discovery (WBD) brings together iconic entertainment, news, and sports brands including HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, and Food Network. Within the SPARK organization, our Hyderabad Machine Learning Engineering team turns first-party audience signals into ML capabilities for identity, audience intelligence, advertising, personalization, forecasting, 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.

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

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

Lead the evolution of Audience Intelligence, including ML Promo Optimizer, STAT v2, lookalike modeling inside Snowflake DCR, and content segmentation.

Own ML architecture for forecasting 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).

What We Offer:

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.