AI Engineer - Sensor Automation

Location:
Tagore Lane

Monday - Friday: 8AM - 5.30PM

A technology‑driven engineering company delivering intelligent automation, instrumentation, and digital solutions for industrial and water infrastructure systems.

• Design and develop ML/AI models for industrial water use cases, including:
  • Sensor anomaly and drift detection
  • Water quality forecasting
  • Predictive maintenance for pumps, valves, and meters
• Build scalable time‑series analytics pipelines for high‑frequency sensor data
• Develop feature engineering pipelines for physical, hydraulic, and signal‑based datasets

• Integrate AI models with IoT platforms, SCADA systems, and edge devices
• Deploy models across cloud and edge environments (containerized or embedded)
• Collaborate closely with firmware and hardware teams to ensure sensor‑aware model design
• Optimize models for latency, reliability, and power efficiency in industrial environments

• Implement MLOps workflows including model versioning, monitoring, retraining, and rollback
• Deploy AI services on cloud platforms such as AWS, Azure, or equivalent
• Design APIs and data services for real‑time and batch inference
• Monitor production model performance and data quality

• Apply physics‑informed ML, hybrid modelling, or graph‑based approaches where relevant
• Translate operational and engineering challenges into AI‑solvable problems
• Prototype, validate, and iterate solutions using real industrial datasets
• Document models clearly for engineering teams, operations, and regulatory review

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Applied Mathematics, or related fields
• Strong proficiency in Python for machine learning and data engineering
• Hands‑on experience with time‑series ML models
• Experience using PyTorch, Tensor Flow, scikit‑learn, or similar frameworks
• Solid foundation in statistics, signal processing, and anomaly detection
• Experience building IoT data pipelines (streaming and batch)
• Familiarity with cloud platforms and containerization (Docker, Kubernetes)
• Understanding of industrial or physical systems (water, utilities, energy, or manufacturing preferred)
• Experience working with sensor data (flow, pressure, vibration, acoustic, environmental)
• Exposure to SCADA, OT systems, or industrial communication protocols is an advantage