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.
We are seeking a Senior Data Intelligence MLOps Engineer to design, build, and maintain the backbone of our Machine Learning lifecycle. You will be responsible for the "industrialization" of AI, moving models from experimental notebooks into robust, production-grade pipelines. Your mission is to automate the journey from raw data curation to model deployment, ensuring our CI/CD cycles are fast, observable, and reproducible.
End-to-End Pipeline Orchestration: Build and manage automated workflows for data preparation, feature engineering, model training, and evaluation.
Machine Learning CI/CD/CT Implementation: Develop Continuous Integration (code testing), Continuous Deployment (model serving), and Continuous Training (retraining triggers) systems.
Infrastructure as Code (IaC): Manage scalable Machine Learning infrastructure using tools like MLFlow
Model Monitoring & Observability: Implement dashboards and alerts for model drift, data skew, and system performance (latency/throughput).
Registry Management: Maintain the Model Registry and Feature Store to ensure versioning and lineage across all experiments.
Security & Compliance: Ensure data privacy and secure access controls throughout the ML lifecycle.
5+ years in DevOps, Data Engineering, or MLOps roles.
Proven Track Record: of taking at least one ML project from a research phase to a high-availability production environment.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
Orchestration Tools: Expertise in Kubeflow, Airflow, Dagster, or Prefect.
Containerization: Mastery of Docker and Kubernetes (K8s) for managing distributed training and inference.
Cloud Platforms: Deep experience with AWS (SageMaker), GCP (Vertex AI), or Azure ML.
Version Control: Advanced Git workflows and experience with DVC (Data Version Control) or MLflow.
CI/CD Frameworks: Experience with GitHub Actions, GitLab CI, or Jenkins specifically for ML artifacts.
Scripting: High proficiency in Python and Bash for automation.
Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
Dyson solves real-world problems and creates better products through the application of engineering, science, design and creativity. It is a family-owned, global technology company, founded by Sir James Dyson who remains at the helm alongside his son Jake.
Since inventing the first cyclonic bagless vacuum cleaner, the DC01, Dyson has consistently invested in research and development to improve its products and technologies radically. Dyson offers products across a growing range of areas: floorcare, air purification, robotics, haircare including formulations, lighting, hand drying, and most recently audio. Dyson continues to expand into new areas.
Today, Dyson sells products in more than 80 markets, has 450 Dyson stores worldwide and is available in all major technology and beauty retailers. Dyson has global headquarters in Singapore and major technology campuses in Singapore, the UK, Malaysia, and the Philippines. Its global team of engineers, scientists and software developers are focused on developing technology-enabled products which work better and which people love to use. Key areas of focus have included high-speed electric digital motors, sensing and vision systems, robotics, machine learning and aerodynamics.
Beyond products, to encourage an inventive future, Dyson is also inspiring the next generation of engineers and inventors through the Dyson Institute of Engineering and Technology, the James Dyson Foundation and the James Dyson Award.
The Dyson family applies its problem-solving approach in other fields, and established Dyson Farming in 2012. It is one of the largest farming businesses in the UK, extending to 36,000 acres across Lincolnshire, Oxfordshire, Gloucestershire and Somerset. It is a family-owned enterprise unlike any other, focussed on long-term investment in British farming and the countryside to grow tasty and nutritious food.
