Director, AI/ML Engineering

Own and drive AI/ML engineering strategy and roadmap aligned with business and customer priorities, including search, recommendations, pricing, forecasting, fraud, and counterfeit detection.

Build, lead, and scale a high-performing ML engineering and applied science team, including hiring, talent development, and resource planning across multiple complex projects.

Set technical direction for ML systems, oversee architecture and model decisions, drive experimentation and A/B testing, and scale ML platforms and MLOps practices for reliable and cost-effective delivery.

10+ years relevant hands-on experience in ML engineering or applied science with production ML systems.

7+ years practical ML or data science experience including computer vision, multi-modal learning, search, or recommendation systems.

5+ years engineering leadership experience managing teams and multiple workstreams.

Experience owning AI/ML roadmaps to deliver measurable customer or business outcomes through cross-functional collaboration.

Strong strategic and technical judgment in model design, architecture, experimentation, and cloud infrastructure balancing performance, speed, and cost.

Proven ability to communicate and influence senior leadership, prioritize tradeoffs, and execute in ambiguous, high-impact environments.

Experience managing multiple ML engineering or applied science teams and familiarity with marketplace, e-commerce platforms, or supply chain contexts especially related to search, recommendations, or fraud detection.