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Canals - ML/AI Engineer

Silver·LATAM·Argentina·mid
mlllm
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ABOUT CANALS Canals builds software for wholesale distributors, helping them operate more efficiently through automation and AI. Our customers are the companies responsible for moving the materials that power the real economy: electrical supplies, plumbing products, roofing materials, HVAC equipment, and more. Every day, thousands of people rely on Canals to help process orders, manage purchasing, handle accounts payable, and streamline critical business workflows. We’re a profitable, rapidly growing company with a team of roughly 100 people distributed across North and South America. We care deeply about building great products, hiring exceptional people, and creating an environment where talented individuals can do the best work of their careers. THE OPPORTUNITY AI is becoming central to how our customers operate, from automating repetitive workflows to making complex operational decisions faster and more accurately. As Canals continues to grow, we’re looking for an ML/AI Engineer to help build and scale intelligent systems across our platform. This is a highly applied role focused on shipping production-grade AI features that create measurable business value. You’ll work at the intersection of machine learning, backend systems, and product engineering, building solutions that improve how wholesale distributors process orders, manage purchasing, classify documents, and automate critical workflows. This role is ideal for engineers who enjoy owning AI products end-to-end: from experimentation and model development to deployment, monitoring, and iteration in production. WHAT YOU’LL DO - Design, build, and deploy AI-powered product features across Canals’ core workflows. - Develop and maintain LLM-powered systems, including agents, retrieval pipelines (RAG), and workflow automation. - Build machine learning models for operational use cases such as classification, forecasting, anomaly detection, and recommendation systems. - Own the full lifecycle of ML systems: data p

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