Machine Learning Engineer II, Hyderabad

Welcome to Warner Bros. Discovery… the stuff dreams are made of.

Who We Are…

When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next…

From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.

Machine Learning Engineer II, Hyderabad

 

About Warner Bros. Discovery: 

Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses. 

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 make 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 

As a Machine Learning Engineer II on the Hyderabad SPARK team, you will be a hands-on builder of production ML systems across WBD’s consumer platforms. You will translate data science ideas into reliable pipelines, models, and services that support identity, audience intelligence, advertising, personalization, forecasting, engagement, and retention use cases. 

You will work closely with senior engineers, data scientists, product managers, and platform teams to build reproducible ML workflows, improve model quality, and help operate models with strong monitoring, governance, and production-readiness practices. 

What You’ll Do :

Technical Execution & Delivery 

• Build and operate low-latency online serving systems for fraud scoring, message decisioning, and real-time personalization. 

• Develop ML models for identity resolution, audience intelligence, content-affinity modeling, genre-preference modeling, and time-series forecasting across global markets. 

• Integrate with personalization and activation systems to consume in-app user signals and deliver model outputs into downstream workflows. 

• Implement feature pipelines that combine 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. 

• Contributes to evaluations of new technologies and approaches, including DCR-native modeling, graph ML, agentic ML orchestration, and LLM-augmented pipelines. 

Production ML Systems 

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

• Contribute to Audience Intelligence capabilities, including ML Promo Optimizer, STAT v2, lookalike modeling inside Snowflake DCR, and content segmentation. 

• Develop and productionize forecasting models 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. 

• Implement MLOps workflows for experiment tracking, model versioning, deployment automation, retraining, monitoring, and drift detection. 

Experimentation, Quality & Observability 

• Implement 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 partner with engineering, data, product, and business stakeholders on mitigation plans. 

• Turn incidents and postmortems into reusable learnings, automated checks, and platform improvements. 

• Apply production-readiness practices such as testability, data quality checks, rollback paths, drift monitoring, and dashboards. 

Cross-functional Partnership & Mentorship 

• Partner with ML leads on execution planning, technical design, capability development, and delivery of production ML systems. 

• Represent the Hyderabad team in technical discussions with ML, Data Engineering, Product, Ad Sales, and US-based stakeholders. 

• Create clear design docs, readiness reviews, runbooks, and postmortem notes that strengthen engineering culture. 

• Support junior engineers through implementation guidance, code reviews, and knowledge sharing. 

What You’ll Bring: 

• 3–5 years of ML engineering experience, or 2+ years with a Ph.D., with demonstrated ownership of production ML components and cross-functional delivery. 

• You are comfortable building components across the ML lifecycle, from problem definition and feature engineering through serving, monitoring, and iteration. 

• You have worked on optimization problems like ranking, personalization, forecasting, or multi-objective decisioning in environments with interacting metrics. 

• You have hands-on experience with Databricks, Spark, SageMaker, Python, and SQL. 

• You have experience in promoting ML models to production for large user populations and applying engineering standards and operational best practices. 

• You have strong proficiency with ML frameworks such as PyTorch, TensorFlow, XGBoost/LightGBM, and scikit-learn, plus solid grounding in statistics and ML fundamentals. 

• Bachelor’s or master’s degree 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 business audiences. 

Preferred 

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

• 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.