Senior Machine Learning Engineer, Hyderabad
Warner Bros. Discovery · Hyderabad
Collected role description
Role overview
Senior Machine Learning Engineer, Hyderabad at Warner Bros. Discovery
Responsibilities
- Build ML models for identity resolution, audience intelligence, content affinity modeling, genre-preference modeling and time-series forecasting across global markets.
- Evaluate new technologies and approaches, including DCR-native modeling, graph ML, agentic ML orchestration, and LLM-augmented pipelines, with clear build/buy/partner recommendations.
- Create clear design docs, architecture reviews, readiness reviews, and postmortems that strengthen engineering culture.
Employment details
- Location: Hyderabad [Telangāna] [India]
Additional role details
- 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.
- 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 & ObservabilityDesign 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 & MentorshipMentor 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.
- 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 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.
- Excellent communication skills, with the ability to explain technical solutions to engineering, science, product, and executive audiences.
- PreferredStreaming / Identity / Fraud / Ad-tech ML: identity resolution, audience modeling, recommendation/ranking, content understanding.
- Hands-on experience with agentic AI frameworks at production scaleExperience with real-time feature serving and low-latency inference, and with mixture-of-experts or graph neural networks.
- Our Technology Stack Primary platform: AWS , Databricks.
- 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.
- 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).
- Languages: Python (primary), SQL, Scala (as needed).
- Championing Inclusion at WBD.
Collected minimum qualification
Master’s or Ph.
Collected experience requirement
5 - 8 years