Lead Data Science & AI Engineer

Charger Logistics Inc. is a world-class asset-based carrier with locations across North America. With over 20 years of experience providing the best logistics solutions, Charger Logistics has transformed into a world-class transport provider and continues to grow.

Charger Logistics invests time and support into its employees, providing them with the room to learn, grow their expertise, and advance their careers. We are an entrepreneurial-minded organization that welcomes and supports individual ideas and strategies.

We are currently seeking a senior, hands-on Lead Data Science & AI Engineer to join our team at our Brampton, Ontario office. This role will architect and lead large-scale ML and AI systems for fleet analytics and logistics optimization, focusing on production-grade machine learning, real-time streaming analytics, and AI-powered decision systems using Google Cloud (Vertex AI, BigQuery), Kafka, and RisingWave.

As a Lead Data Science & AI Engineer, you will design, build, and scale advanced ML and AI solutions for real-time fleet optimization, predictive maintenance, anomaly detection, and intelligent decision-making. This is a pure data science and ML engineering role, focused on solving complex logistics and telematics problems at scale using cloud-native and streaming architectures.

You will serve as the technical leader for ML initiatives, owning system architecture, model strategy, and production deployment while collaborating closely with product, engineering, and DevOps teams.

Responsibilities :

Machine Learning & Predictive Modeling

• Design and deploy ML models for route optimization, ETA prediction, fuel efficiency, and fleet utilization.
• Build anomaly detection systems for trip deviations, fuel theft, vehicle health, and driver behavior.
• Develop time-series forecasting models for demand planning, maintenance, and capacity optimization.
• Implement reinforcement learning and optimization models for dynamic routing.

Real-Time & Streaming ML

AI & LLM Solutions

ML Platform & MLOps

Data Engineering for ML

Technical Leadership

Requirements

Nice to Have :

Why This Role?

Benefits