Machine Learning Engineer – Supply Chain & IoT Solutions

Role Overview

Join our team as a Machine Learning Engineer to design and implement AI-driven solutions that optimize operations and enhance predictive capabilities across our platforms. Collaborate with technical leadership to develop models that improve efficiency, forecasting, and decision-making within supply chain and IoT domains.

Responsibilities

• Design and deploy machine learning models focused on risk prediction, anomaly detection, and operational optimization.
• Develop sophisticated algorithms for pattern recognition, predictive maintenance, and demand forecasting.
• Train and fine-tune models using diverse real-world operational data sets.
• Continuously evaluate and enhance model performance to ensure accuracy and reliability.
• Collaborate with architects to seamlessly integrate ML solutions into production systems.

Required Skills

• Strong expertise in ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Proficiency in Python and data processing libraries like pandas and NumPy.
• Experience with methodologies in classification, regression, and time-series forecasting.
• Knowledge of feature engineering, model optimization, and anomaly detection techniques.
• Familiarity with the ML lifecycle management, including training, validation, and deployment.

Nice to Have

• Experience with computer vision or IoT data analytics.
• Background in supply chain optimization or resource management.
• Knowledge of sustainability metrics and efficiency modeling.

Why Join?

Focus on core ML development while our team handles deployment, allowing you the freedom to innovate. Your contributions will directly impact how businesses and users leverage AI for smarter, more efficient operations.