AI Scientist Transportation & Logistics

About the Role

About Avathon

We’re hiring a 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 an experienced 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.

Key Responsibilities 

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 

• 6+ years of experience in AI/ML or optimization, or Supply Chain planning systems

Strong expertise in: 

• Python (NumPy, Pandas, PyTorch/TensorFlow) 


• Optimization tools (Gurobi, CPLEX, OR-Tools) 


• Deep knowledge of: 


• Routing algorithms (VRP, shortest path, heuristics/metaheuristics) 


• 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 constraints 

• Communication skills to explain complex models to business stakeholders 

Publications / Patents: 

• Strong plus if you have published in AI/ML/OR conferences (NeurIPS, ICML, INFORMS, etc.) 

Interview Process

As part of the interview process, you will be asked to complete a technical assessment. Expect atleast two-three rounds of Technical interviewing rounds and one onsite round.  

Contract and temporary roles are not eligible for the above benefits.

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