Senior Machine Learning Engineer (Consumer Team), Hyderabad

Senior Machine Learning Engineer (Consumer Team), Hyderabad

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.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.