Senior AI Scientist – Transportation & Logistics

Senior AI Scientist – Transportation & Logistics

Pleasanton, California, United States

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.

Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Work on AI-driven projects that drive real change across industries and improve lives.

We're hiring a Senior AI Scientist (Transportation & Logistics) at Avathon — where AI meets the real world. This is a high-impact role at the intersection of operations research, reinforcement learning, and large-scale data systems, focused on building intelligent solutions that transform transportation and logistics networks.

We are looking for a Senior AI Scientist to lead the design and deployment of advanced optimization and machine learning systems across complex transportation ecosystems. You will work on real-world challenges such as routing, scheduling, network optimization, demand forecasting, and asset utilization across multimodal logistics environments including FCL, LCL, FTL, LTL, intermodal, and maritime transportation.

This role offers the opportunity to drive innovation in vessel scheduling, container repositioning, fleet optimization, and dynamic routing, while collaborating closely with engineering, product, and operations teams to bring scalable AI solutions into production.

AI/ML Model Development

• Design and implement advanced models for:
• Fleet optimization and capacity planning
• Vehicle routing and scheduling (VRP, TSP variants)
• Demand forecasting and optimization
• Apply reinforcement learning, optimization algorithms, and hybrid ML + OR approaches

Transportation Domain Solutions

• Build solutions for:
• Maritime logistics (vessel scheduling, port operations)
• Container repositioning and imbalance optimization
• Truckload (FTL), less-than-truckload (LTL), and intermodal routing
• Incorporate real-world constraints (time windows, capacity, regulations, SLAs)

AI Engineering & Deployment

• Productionize models using scalable architectures (cloud-native, APIs)
• Collaborate with engineering teams to deploy AI solutions into production
• Ensure robustness, explainability, and monitoring of models

Data & Feature Engineering

• Work with large-scale datasets:
• Shipment data, GPS/telematics, weather, port congestion, tariffs
• Build feature pipelines and data validation frameworks

Leadership & Strategy

• Lead AI initiatives and mentor junior scientists
• Translate business problems into AI solutions
• Partner with product, operations, and stakeholders to define roadmaps

Required Qualifications

• PhD in Computer Science, Operations Research, Applied Math, or related quantitative field
• 10–15+ years of experience in AI/ML or optimization, or Supply Chain planning systems

Strong expertise in:

• Python (Num Py, Pandas, PyTorch/Tensor Flow)
• Optimization tools (Gurobi, CPLEX, OR-Tools)
• Routing algorithms (VRP, shortest path, heuristics/meta heuristics)
• Time-series forecasting and probabilistic modeling
• Experience deploying models in production environments

Preferred Qualifications

• Experience in transportation, logistics, or supply chain domain
• Familiarity with Maritime shipping or fleet scheduling
• Container logistics and repositioning problems

Experience with:

• Reinforcement learning for dynamic decision-making
• Digital twins and simulation systems
• Knowledge of cloud platforms (GCP, AWS, Azure)
• Experience…