Senior AI/ML Engineer

About the job

Responsibilities: • Lead the architecture and development of AI/ML models for HVAC fault detection, targeting 95%+ accuracy on the top 25 fault types. • Design and implement weak supervision strategies using rule-based "Silver Labels" and technician-verified "Gold Labels". • Build and optimise classification models (Random Forest, XGBoost, neural networks) for time-series anomaly detection. • Develop model interpretability features that explain fault predictions with underlying decision data. • Establish data normalisation and segmentation strategies for environmental conditions (temperature, humidity profiles). • Design human-in-the-loop feedback systems for continuous model improvement. • Collaborate with data engineers on data pipeline requirements and feature engineering. • Define model evaluation metrics, conduct failure analysis, and iterate on model performance. • Mentor mid-level ML engineers and establish best practices for ML development. • Stay current with SOTA approaches in time-series analysis, anomaly detection, and industrial AI.

Requirements

• Python
• ML frameworks
• time-series analysis
• anomaly detection
• predictive maintenance systems

Qualifications

• 6+ years of professional experience in machine learning engineering
• Strong expertise in Python and ML frameworks
• Experience with time-series analysis
• Deep understanding of supervised and unsupervised techniques
• Experience with IoT data pipelines

Preferred Technologies

• Python
• ML frameworks
• time-series analysis
• anomaly detection
• predictive maintenance systems