Senior Machine Learning Engineer, Hyderabad

Storytelling is, and will always be, the heart of what we do at Skydance

Our vision is to build a thriving entertainment ecosystem where stories and worlds are imagined, brought to life and experienced. We create for every age and audience, anchored by the strength of our content and experiences and the depth of our connection with fans. We are creator-first, audience-focused, tech-forward, globally scaled.

Here, you’ll work with talented teams that move fast, think boldly and collaborate with purpose to deliver results. We aim high, champion the best ideas and win together, earning the trust of our employees, creators, partners and audiences every day.

If you’re energized by the opportunity to help build the next-generation global media and entertainment company powered by creativity and technology, we’d be thrilled to welcome you aboard. LET’S GO!

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Senior Machine Learning Engineer, 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 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

About Skydance

Skydance is a next-generation global media and entertainment company, comprised of three business segments: Studios, Direct-to-Consumer, and TV Media. Skydance's portfolio unites legendary brands, including Paramount, Warner Bros., HBO and HBO Max, Paramount+, Pluto TV, CBS, CNN, CBS Sports, TNT Sports, Nickelodeon, Cartoon Network, MTV, Food Network, BET, HGTV, and Comedy Central.

Some Important Details

We embrace 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. In line with the laws of the country or region in which the role is based, this includes consideration without regard to race, color, ethnicity, national origin, citizenship status, religion or belief, sex, gender, gender identity or expression, sexual orientation, age, marital status, pregnancy, parenthood, physical or mental disability, genetic information, military or protected veteran status, union status or any other category protected by applicable 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.