- Data Science and Engineering
- Singapore - Technology Centre
ABOUT THE ROLE
Dyson’s multidisciplinary Energy Storage development team is responsible for delivering cells from early prototypes in the UK, through to volume manufacture in a Singapore plant. The cells that the team delivers will push the boundaries of performance, power density, and efficiency. These cells will drive new high value Dyson products with step improvements over our competitors.
Dyson Global IT are seeking an MLOps Engineer who will be responsible for the deployment and management of machine learning models and algorithms. They will work closely with the project team and external stakeholders to ensure that the models are optimised and can be deployed within the project’s overall architecture.
The MLOps Engineer will be responsible for packaging, deploying, and managing the machine learning models and algorithms. They will also be involved in monitoring, troubleshooting, and resolving any issues that arise, and will be responsible for ensuring that all models and algorithms are secure and compliant with data security regulations.
Previous experience in MLOps and machine learning is essential for this role. Strong analytical and problem-solving skills are key, as project requirements may evolve over time and the MLOps Engineer will need to be able to adapt and improve the models and algorithms accordingly.
- Package, deploy and manage machine learning models and algorithms.
- Build automated pipelines for the deployment and management of the models and algorithms.
- Support data scientists and engineers in the training and validation of the models and algorithms.
- Collaborate with other teams to ensure that models and algorithms are integrated with the project’s overall architecture.
- Monitor, troubleshoot, and resolve any issues that arise with the models and algorithms.
- Analyse performance metrics to identify areas for improvement.
- Ensure that all models and algorithms are secure and compliant with data security regulations.
- Identify and implement new technologies and tools to improve the MLOps process.
- Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field.
- Proficiency in one or more programming languages such as Python or R
- and knowledge in common data structures and algorithms.
- 2+ years of experience in data science and machine learning. Familiarity with machine learning frameworks such as TensorFlow, PyTorch or Keras.
- Strong core knowledge of applied machine learning such as supervised and unsupervised learning and deep learning.
- Proven track-record of using a rigorous, scientific approach to model building, testing and validation.
- Strong experience with containerization of code using Docker.
- Experience with Python and Shell scripting.
- Fluent in Git and familiar with CI/CD/CT practices to develop and deliver software optimally.
- Keen understanding of data models and ETL/ELT processes.
- Solid experience with enterprise data science platforms in cloud environments such as AWS, GCP, or Azure and the relevant PaaS and MLOps offerings.
- Strong understanding of data security and privacy regulations.
- Ability to work independently and as part of a team.
- Passion for learning new technologies and techniques.
- Excellent communication and interpersonal skills.
- Has a passion to understand Dyson, to frame its problems, and to deliver tactical solutions in short timeframes when required.
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.