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 real constraints such as time windows, capacity, regulations and SLAs
• Solve maritime and container problems, including vessel scheduling, port operations and container repositioning
• Combine OR, reinforcement learning and ML where a single method falls short

Prediction

• Build ETA and transit time models by lane, mode, carrier and season, using shipment events, GPS and telematics, weather and port congestion
• Flag shipments, carriers and suppliers that move away from normal behavior, and forecast clear-to-build risk days in advance
• Model the trade-off between expedite cost and production impact so recommendations make business sense

Productization and Leadership

• Put models into production with engineering on cloud-native services, with monitoring, explanations and data validation
• Use graph features from the Computational Knowledge Graph and work with AI agents that triage exceptions and recommend actions
• Lead AI initiatives in the domain, mentor scientists and help product set the roadmap

You'll Have

• PhD in Operations Research, Computer Science, Applied Math, Transportation Engineering or a related field
• 10+ years in AI, ML, optimization or supply chain systems
• Deep knowledge of routing algorithms (VRP, shortest path, heuristics and metaheuristics) and time series and probabilistic forecasting
• Hands-on Python (NumPy, pandas, PyTorch or TensorFlow) and optimization solvers (Gurobi, CPLEX, OR-Tools)
• Experience shipping models to production on real logistics data, ideally at a TMS, visibility or freight vendor such as Oracle, Blue Yonder, Manhattan, project44, FourKites or Flexport, or at an industrial shipper
• Maritime, container logistics or fleet scheduling experience is a strong plus
• Reinforcement learning, simulation or digital twins, and streaming data (Kafka, Spark) are a plus
• Publications at NeurIPS, ICML, INFORMS or similar are a plus

Compensation

Pay Range: $160k - $240k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.

Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week.