AI Research Engineer 6 - TL, Algo Core - AI for Member Systems

Drive the team's technical vision and roadmap for reward modeling, utility estimation, and multi-objective optimization — including auction-based and constrained-optimization approaches to allocating promotional real estate. Drive cross-functional partnerships with Merchandising, Ads, MECS, Product, and Data Science & Engineering to align AI/ML capabilities with business priorities. Partner with the Personalization Foundations team to integrate and leverage the utility layer, reward signals, and multi-objective optimization across all member-facing AI models. Design and run rigorous offline experiments and A/B tests to validate the impact of new reward, utility, and multi-objective optimization systems on key business and member-experience metrics. Contribute to the team's technical culture through mentorship, code review, and raising the bar on engineering practices. 6+ years of experience applying machine learning in an industry setting, with a track record of delivering impactful production systems. Experience driving successful partnerships with both technical and nontechnical stakeholders. Master's or PhD in a computational field such as computer science, statistics, math, operations research, or physics. Deep expertise in ML and optimization algorithms and frameworks, with hands-on experience training, tuning, and deploying models in production. Experience with reward modeling, utility estimation, or constrained-optimization and auction-based allocation systems. Strong software engineering skills in Python, plus experience with Scala or Java. Strong 80/20 mindset: ability to scope the right problem, ship pragmatically, and maintain rigorous standards without over-engineering.