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Tier-1 brand, mid-level ML title, metro location and broad skills create high applicant density.
Role requires specialized ad-tech and identity ML experience reducing cross-industry transferability.
Explicit 5-8 years requirement and specific Databricks/AWS/ML stack make screening stringent.
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Lead design and operation of low latency online ML serving systems for fraud scoring, personalization, and message decisioning.
Architect and evolve ML systems for identity resolution, audience intelligence, forecasting, and personalization across global markets.
Mentor junior engineers and collaborate cross-functionally to translate business problems into robust ML solutions with measurable impact.
5-8 years ML engineering experience or 2+ years with Ph.D. including senior-level ownership and cross-team impact.
Proven experience with Databricks, Spark, and AWS Sagemaker for production ML system architecture.
Master's or Ph.D. in Computer Science, Statistics, Machine Learning, or related field (or equivalent industry experience).
Expertise in ML frameworks (PyTorch, TensorFlow, XGBoost/LightGBM, scikit-learn) and strong statistics and ML fundamentals.
Experience owning end-to-end ML systems beyond modeling to include serving, monitoring, and continuous improvement.
Background in optimization problems like ranking, personalization, multi-objective decisioning, preferably in large-scale production environments.
Skilled in advanced ML areas such as real-time feature serving, graph neural networks, agentic AI workflows, and identity resolution or ad-tech ML domains.