Machine Learning Engineer II ML), Hyderabad

Within the Data & Audience Platform organisation, the Machine Learning Engineering team builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalisation across WBD brands, turning first-party signals from hundreds of millions of viewers into production ML systems. The role is hands-on and sits alongside Senior and Staff engineers, with responsibility for building and maintaining production ML pipelines, contributing to model development, and bridging data science and software engineering.

The successful candidate will work on high-impact ML systems at scale - from probabilistic identity graphs to single-title affinity models - and develop deep expertise across the full ML lifecycle.

• Build and maintain end-to-end ML pipelines for training, evaluation, and batch inference across use cases such as identity resolution, audience segmentation, and content affinity modelling.
• Implement and experiment with supervised, unsupervised, and ranking models in Python using scikit-learn, XGBoost/LightGBM, and PyTorch.
• Engineer features from first-party viewership, engagement, subscription, and behavioural signals, guarding against data leakage, collinearity, and training/serving skew.
• Run structured offline experiments, evaluate them with appropriate metrics (precision/recall, F1, AUC-ROC, calibration, lift), and document findings in MLflow.
• Develop and maintain data and feature pipelines on Databricks (PySpark, Delta, Workflows) that feed the feature store and model-training workflows, with attention to idempotency and reproducibility.
• Write clean, tested, production-quality Python following engineering best practices such as unit tests, code reviews, and CI/CD.
• Use MLflow for experiment tracking, model registration, and versioning under the guidance of senior engineers.
• Support deployment and monitoring of batch inference jobs integrated with downstream activation platforms (e.g. Mosaic, Free Wheel, GAM) and data in Snowflake.
• Use AI-assisted development tools (Cursor, Git Hub Copilot, Amazon Q) and Databricks Genie or Snowflake Cortex to accelerate coding, debugging, documentation, and data exploration, applying prompt-engineering patterns and participating in the evaluation of MCP tooling.
• Partner with Senior and Staff MLEs on system-design decisions, work cross-functionally with Data Engineering, Feature Engineering, and Analytics to ensure data quality and pipeline reliability, and document models, pipelines, and experiments for team knowledge sharing.

• 2-4 years of industry experience in machine learning, data science, or ML engineering (or 1-2 years with a relevant M.S.).
• Strong Python proficiency, with experience using pandas, Num Py, scikit-learn, and at least one deep-learning framework (PyTorch or Tensor Flow).
• Hands-on experience with Spark/PySpark or equivalent large-scale data processing.
• Proficiency in SQL and familiarity with cloud data warehouses or lake houses such as Snowflake or Databricks.
• Experience with experiment-tracking tools such as MLflow, Weights & Biases, or similar.
• Solid grasp of core ML concepts including classification, regression, ranking, embeddings, and model evaluation.
• Strong computer science fundamentals, including data structures, algorithms, and clean code.
• Bachelor's degree in Computer Science, Statistics, Engineering, or a related quantitative field, or equivalent practical experience.
• Ability to use AI tools to independently improve productivity across the ML lifecycle.
• Clear written and verbal communication.

• Experience with Databricks (notebooks, Delta Lake, Workflows/DLT, Unity Catalog, MLflow).
• Exposure to recommendation systems, audience segmentation, identity resolution, or forecasting.
• Familiarity with AWS services (Sage Maker, S3, Lambda) and/or feature stores (Databricks Feature Store, Feast).
• Exposure to agentic AI tools such as Cursor, Git Hub Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, or MCP.

• A great place to work.
• Fast-track growth opportunities.

The company's guiding principles are discussed with candidates during the interview process.

Discovery is a premier global media and entertainment company offering audiences the world's most differentiated and complete portfolio of content, brands and franchises across…