Senior IoT Data & AI Engineer - Kitchen Analytics

Airedale Solutions Ltd.; United Kingdom; Hybrid; GBP 90.000 - 125.000; Vollzeit

Benefits dieser Stelle

Bonus

Permanent Contract

23 days + bank holidays

Hybrid working

Zusammenfassung

A Senior IoT Data & AI Engineer role at The Airedale Group involves turning proven analysis into reliable systems. You will co-work with the CTO and IoT data analyst to build the data platform, predictive models and automated reporting for early failure detection across UK hospitalities estates.

You will handle end-to-end delivery, collaborate with a small team, and ensure governance and explainability while deploying models and reporting through APIs and data layers.

Qualifikationen

• Strong Python and SQL, with production experience building and operating data pipelines on a lakehouse platform.
• Hands-on experience with time-series, sensor or telemetry data at scale, including data gaps, drift and misbehaving devices.
• Applied anomaly detection or predictive modelling taken into production with robust and explainable methods.
• Experience building with LLM APIs beyond chat: retrieval, tooling, reporting, and evaluation of model outputs.

Aufgaben

• Take anomaly detection work from PoC into production across the estate, enabling live early warning.
• Build a validation loop linking alerts to engineer findings to measure detection accuracy.
• Develop a failure-signature library from telemetry and service history to strengthen predictions.

Kenntnisse

Python

SQL

Data pipelines

Time-series data

Anomaly detection

LLM APIs

End-to-end delivery

Communication

Tools

ThingsBoard

Microsoft Fabric

Databricks

dbt

Jobbeschreibung

A Senior IoT Data & AI Engineer role at The Airedale Group involves turning proven analysis into reliable systems. You will co-work with the CTO and IoT data analyst to build the data platform, predictive models and automated reporting for early failure detection across UK hospitalities estates.

You will handle end-to-end delivery, collaborate with a small team, and ensure governance and explainability while deploying models and reporting through APIs and data layers.