Hiring: Senior Machine Learning Engineer Company: Warner Bros. Discovery Location: New York, NY Job Posted Time: 2026-09-12 13:16:53 Target Skills & Keywords : A/B Testing, AWS, Data Pipeline, Databricks, Delta Lake, Feature Store, GitHub, LLM, Lambda, LangChain, LightGBM, MLOps, MLflow, Machine Learning, PySpark, Python, RAG, S3, SQL, SageMaker, Scala, Snowflake, Systems Design, XGBoost About the job Experience: •8 years of industry experience in ML engineering or applied data science •3+ years with a Ph.D.), including a track record of leading projects to production. Required Skills: •ML System Design & Technical Leadership •Lead end-to-end development of production ML systems: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring. •Tower retrieval), lookalike modeling, or forecasting — and drive their technical direction. •Make and document key architectural decisions across a workstream •(feature-store design, training/serving patterns, evaluation frameworks) •Provide deep trade-off analysis on scalability, latency, reliability, and cost. •Design scalable feature and inference pipelines on Databricks (PySpark, Delta, Workflows/DLT, Unity Catalog) integrated with Snowflake and activation systems (Mosaic, FreeWheel, GAM), with documented feature contracts, backfill paths, and freshness SLAs. •Establish and evangelize patterns that other engineers adopt; anticipate risks and failure modes before they surface. Qualifications: •Recommendation systems, personalization, identity resolution, or audience modeling in a media / streaming / ad-tech context. •Resolution (graph-based matching, entity resolution, confidence calibration), and Data Clean Room ML (Snowflake DCR, AWS Clean Rooms). •Used by multiple engineers or teams. •Applied hands-on capability in agentic AI frameworks (LangChain, LangGraph, AutoGen, MCP), Databricks Genie Space configuration, and Snowflake •And contributions to open source or ML publications. •Primary platform: Databricks (Lakehouse, PySpark, Delta, Workflows/DLT, MLflow, Feature Store, Unity Catalog, Asset Bundles, Genie). Cloud: AWS •(SageMaker, S3, Lambda). Warehouse: Snowflake (incl. DCR, Snowpark, Cortex). •Activation: Mosaic, FreeWheel, Google Ad Manager. Agentic AI: Cursor, GitHub •Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, MCP. Languages: Python •(primary), SQL, Scala (as needed). Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!