Lead Data Intelligence Machine Learning Engineer

About the role

Dyson’s Data Intelligence team in Dubai is seeking a Lead Machine Learning Engineer to drive the automation of data‑labelling pipelines. You will design tools that minimise manual annotation by applying active learning, weak supervision and synthetic data techniques, ensuring high‑quality, model‑ready datasets for next‑generation connected products.

Key responsibilities

• Architect end‑to‑end automated labelling systems using frameworks such as Snorkel, Cleanlab or custom active‑learning loops.
• Develop Human‑in‑the‑Loop interfaces where models pre‑label data and humans review only high‑uncertainty samples.
• Implement quality‑assurance checks to detect and correct noisy or mislabelled data.
• Collaborate with software engineers to integrate labelling tools with existing data lakes and MLOps infrastructure.
• Fine‑tune teacher models to generate pseudo‑labels for student models and maintain robust data preparation pipelines.
• Perform data visualisation, feature engineering and in‑depth analysis to support research and product deployment.

Required profile

• 8+ years of professional experience in machine‑learning engineering, preferably on data‑centric AI, computer‑vision or NLP pipelines.
• Proven track record of building automated labelling solutions and working with large‑scale datasets.
• Strong collaboration skills to work with data scientists, software engineers and product teams.

Required skills

• Python
• PyTorch or TensorFlow
• NumPy, Pandas, Scikit‑learn
• Snorkel, Cleanlab
• Active Learning, Weak Supervision, Synthetic Data Generation
• Data Lakes, MLOps pipelines
• Data visualisation and feature engineering