We are looking for a Machine Learning Engineer to transform 8 years of logistics IoT data into AI-powered insights and customer-facing intelligence. You will work with large-scale telematics data including GPS locations, trips, fuel usage, vehicle activity, orders, and operational events to build intelligent systems such as anomaly detection, benchmarking, and proactive insights tailored to different customer personas. This role is focused on turning raw operational data into practical, actionable AI solutions that help customers reduce costs, improve efficiency, and make better operational decisions.
Build AI-Powered Customer Insights • Develop anomaly detection models for logistics and fleet operations • Identify patterns such as fuel inefficiencies, underutilized vehicles, abnormal trips, and driver behavior drift • Build proactive insight systems that surface recommendations automatically
Industry Benchmarking & Intelligence • Create benchmarking models comparing fleets across industries, vehicle types, and usage patterns • Develop scoring and performance indicators for customers • Build customer persona-based insights (Operations, Finance, Fleet Managers, etc.)
Work with Large-Scale IoT Data • Process high-volume telematics data (GPS, trips, fuel, sensors, orders, etc.) • Build data pipelines for training and inference • Design scalable model deployment and monitoring systems
Productionize Machine Learning Models • Deploy models into production systems • Monitor model performance and data drift • Continuously improve model accuracy and relevance
Collaborate Across Teams • Work closely with Product, Data, and Engineering teams • Translate business problems into ML solutions • Help shape the company’s AI roadmap
Must Have • 3+ years experience in Machine Learning or Data Science roles • Strong Python skills (Pandas, NumPy, Scikit-Learn, etc.) • Experience with time-series data or anomaly detection • Experience working with large datasets and data pipelines • Understanding of model deployment and production environments • Strong problem-solving and analytical thinking
Nice to Have (But Not Required) • Experience with IoT, telematics, or logistics data • Experience with forecasting or time-series models • Experience with clustering, anomaly detection, or unsupervised learning • Experience with cloud platforms (AWS, GCP, etc.) • Experience with real-time or streaming data systems
© 2026 HyreTech. All rights reserved.