avathon · Pleasanton, California, United States
Skills: Python
Who We Are & Why Join Us Avathon is the leading Industrial AI autonomy platform, helping customers across heavy industries -- energy, mining, manufacturing, aerospace, defense, and logistics -- accelerate the journey toward autonomous operations. Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured, and machine vision data to power AI-driven applications in asset performance management, supply chain intelligence, visual AI, and global trade management. With capabilities spanning digital twins, normal behavior modeling, natural language processing, and computer vision, Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale. Cutting-Edge AI Innovation -- Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment -- Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact -- Work on AI-driven projects that drive real change across industries and improve lives. Learn more at: avathon.com We are hiring a Senior AI Scientist to build the optimization and machine learning models behind Logistics and Transportation on the Avathon platform. You will work on routing, scheduling, network optimization, ETA prediction and asset utilization across FTL, LTL, intermodal and maritime networks, including vessel scheduling and container repositioning. Our models run on top of a Computational Knowledge Graph that links shipments to the orders, parts and production they affect, so you can measure impact, not just delay. This role sits in Product Engineering. You will take models from research to production with the Logistics engineering team. You Will Optimization Build fleet optimization, capacity planning and vehicle routing and scheduling models (VRP and its variants) with…
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