StaffAppliedScientist

Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers. By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise. Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U. S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone. If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us. About the Role The Afresh Intelligence team is responsible for the development and performance of AI/ML models that power our core replenishment technology. Our models are directly responsible for ordering millions of dollars of fresh inventory across the world every day. Fresh food ordering is an extremely complex high-dimensional decision-making problem, and we face the complex challenges presented by decaying product, uncertain shelf lives, varying consumer demand, stochastic arrival times, extreme weather events, and tight performance constraints (to name a few). We tackle these problems with a mix of machine learning, large-scale simulation, and optimization technologies. We are looking for a Staff Applied Scientist to lead R for candidates with a PhD, 4+ years of industry experience. Experience researching and building systems that support large-scale decision making under uncertainty. Prior experience in areas such as inventory optimization, supply chain management, network optimization, forecasting, game theory, decision analysis, stochastic optimization, approximate dynamic programming, o