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Tier-1 brand plus metro location increase competition, while senior specialization reduces applicant density.
Role requires ad-tech identity resolution and production ML expertise, limiting cross-industry transferability.
Explicit senior years plus mandatory production ML stack and specialized ad-tech experience make filters stringent.
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Lead architecture and development of production ML systems focused on probabilistic identity resolution, audience intelligence, personalization, forecasting, and real-time feature pipelines.
Own end-to-end ML solutions from model development through serving, monitoring, and continuous improvement across global consumer platforms.
Mentor and guide engineers, define scalable patterns for ML pipelines, deployment automation, quality, observability, and promote engineering standards.
9-13 years ML engineering experience or 6+ years with Ph.D., with demonstrated senior technical leadership and ownership.
Master’s or Ph.D. in Computer Science, Statistics, Machine Learning, or equivalent industry experience.
Hands-on expertise with Databricks, Spark, Sagemaker, and ML frameworks including PyTorch, TensorFlow, XGBoost/LightGBM, scikit-learn.
Experience designing and operating low-latency online serving systems, real-time feature pipelines, and production ML systems for large user populations.
Proven ability to architect and scale complex ML systems including identity resolution and audience modeling in media or advertising domains.
Experience with optimization problems such as ranking, personalization, or multi-objective decisioning with interacting metrics.
Comfortable driving cross-functional partnerships, setting technical standards, and mentoring senior engineers in a fast-paced production environment.