What You’ll Do

Machine Learning & Modeling

• Drive the Deep Learning Evolution: Lead the architectural transition from legacy tree-based models (XGBoost) to advanced Neural Network architectures (Deep Learning) for audience propensity, lookalike modeling, and real-time segmentation.
• Own Value-Based Bidding (ROAS): Evolve our bidding strategy from simple conversion prediction to sophisticated ROAS-based optimization, developing models that predict user value (LTV) to maximize client returns within dynamic auction environments.
• Champion Agentic AI & Automation: Spearhead the exploration and adoption of autonomous agentic workflows to enhance decisioning and operational efficiency, moving beyond static models to self-correcting systems.
• Build Production Deep Learning Systems: Oversee the end-to-end engineering of high-scale inference pipelines, including embedding layers, real-time feature stores, and low-latency serving infrastructure such as ONNX, TensorRT etc.
• Advance MLOps & Experimentation: Establish rigorous MLOps practices for model versioning and drift detection while shifting further into multi-armed bandit strategies (Exploration vs. Exploitation) that optimize directly for business outcomes (Revenue/GP) rather than just model metrics. 
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