Job Description
The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities).
About the Role
As an ML Platfor...
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