Data Intelligence MLOps Engineer

About the role

Dyson is looking for a Data Intelligence MLOps Engineer to design, build and maintain the core of its machine‑learning lifecycle. You will turn experimental notebooks into robust, production‑grade pipelines that power the next generation of connected devices.

Key responsibilities

• Build and manage automated end‑to‑end workflows for data preparation, feature engineering, model training and evaluation.
• Develop CI/CD/CT systems for code testing, model serving and automated retraining triggers.
• Implement Infrastructure as Code to provision scalable ML infrastructure using tools such as MLflow.
• Create dashboards and alerts to monitor model drift, data skew and system performance.
• Maintain the Model Registry and Feature Store to ensure versioning and lineage.
• Enforce data privacy and secure access controls throughout the ML lifecycle.

Required profile

• 3+ years of experience in DevOps, Data Engineering or MLOps.
• Proven track record of moving at least one ML project from research to high‑availability production.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or a related field.

Required skills

• Python
• Kubeflow, Airflow, Dagster or Prefect
• Docker and Kubernetes
• AWS SageMaker, Google Cloud Vertex AI or Azure ML
• Git, DVC and MLflow
• GitHub Actions, GitLab CI or Jenkins