Senior AI Scientist – Transportation & Logistics
Listed on 2026-04-17
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IT/Tech
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer, Data Engineer
Overview
Who We Are & Why Join Us
Avathon is the only physical AI unicorn headquartered in the San Francisco Bay Area. We go beyond models and dashboards; we deploy AI that continuously computes across supply chains, energy systems, and industrial operations. Our Operational Technology platform turns fragmented data into real-time, autonomous decisioning across the systems that power the global economy. This is not digital AI. This is AI for operational reality where latency, constraints, and failure have real-world consequences.
Why Avathon
- 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
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)
- Deep knowledge of:
- 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 with streaming data (Kafka, Spark)
Key Skills
- Optimization + Machine Learning hybrid modeling
- Strong problem-solving and mathematical modeling skills
- Ability to handle ambiguous, real-world…
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