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Dyson
AI

Data Intelligence Machine Learning Engineer

Dyson · Dubai, DU, AE

Actively hiring Posted 3 months ago

Role overview

Salary:

Competitive

Job Family:

Product Software Engineering

Location:

United Arab Emirates - Dubai Office

Responsibilities

  • Architect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.
  • Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.
  • Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.
  • Tooling & Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.
  • Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.
  • Set up and maintain robust data preparation infrastructure—optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.
  • Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You’ll help transform raw data into actionable insight, supporting both research and deployment.
  • Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.

About the company

At Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.

You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.

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Machine Learning Robotics Ai
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