Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.
Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact.
Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.
Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.