Data Intelligence Machine Learning Engineer

Dyson
Dubai
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsSkills: ["Communication","Collaboration"]

Design and implement automated data labelling pipelines that reduce manual annotation, using active learning, weak supervision, and synthetic data generation. Build human-in-the-loop workflows, denoising and quality checks, and fine-tune teacher models for pseudo-labels. Collaborate with engineers to integrate labelling tools with data lakes and MLOps, while performing visualization and feature engineering to turn raw data into model-ready datasets at scale.

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Dyson
Dyson
1 month ago

Data Intelligence Machine Learning Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 38 days agoStatus: Live
Reposted: similar role first listed 5 months ago

Job Summary

Design and implement automated data labelling pipelines that reduce manual annotation, using active learning, weak supervision, and synthetic data generation. Build human-in-the-loop workflows, denoising and quality checks, and fine-tune teacher models for pseudo-labels. Collaborate with engineers to integrate labelling tools with data lakes and MLOps, while performing visualization and feature engineering to turn raw data into model-ready datasets at scale.
Location: Dubai
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Architect end-to-end automated data labelling pipelines using tools like Snorkel/Cleanlab or custom active learning loops.
  • •Build human-in-the-loop interfaces/workflows where models pre-label and humans review high-uncertainty samples.
  • •Implement quality assurance and denoising methods to detect and correct mislabelled/noisy data.
  • •Collaborate with software engineers to integrate labelling tools with existing data lakes and ML training infrastructure.
  • •Set up and maintain data preparation infrastructure and support model optimization with teacher/student fine-tuning and pseudo-labels.

Key Requirements

  • •At least 3+ years of professional experience in machine learning engineering focused on data-centric AI or computer vision/NLP pipelines.
  • •Proficiency in Python and ML/data libraries including PyTorch (or TensorFlow), NumPy, Pandas, and scikit-learn.
  • •Experience with weak supervision (labelling functions) and/or active learning strategies like uncertainty sampling and diversity sampling.
  • •Hands-on data engineering skills using SQL and NoSQL, managing large-scale unstructured data such as images, text, or audio.
  • •Familiarity with cloud ML/labeling services (AWS SageMaker Ground Truth, GCP Vertex AI, or Azure ML) and tools like DVC for data version control.
Experience:3+ years
Skills:CommunicationCollaboration
Tech Stack:PythonPyTorchTensorFlowNumPyPandasScikit-learnSnorkelCleanlabSQLNoSQLAWSSageMaker Ground TruthGCPVertex AIAzure MLDVCJupyterTableauPower BIJupyter Notebook

Company Brief

Dyson
Designs and manufactures innovative home appliances including vacuum cleaners, air purifiers, hand dryers, hair care products, and heaters using advanced engineering and proprietary technologies focused on performance and design.
Industry: Home Appliances
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Established Company
Funding: Bootstrapped
Headquarters: Malmesbury, United Kingdom
Founded: 1991
WebsiteLinkedIn