- SGD Competitive Remuneration Package
- Robotics and Machine Learning, Research Engineering
- Singapore - Singapore
Dyson is a global technology company. We examine what currently exists and question it. We take things apart and look at them from new angles. We reinvent things that should simply work better. The Machine Learning team works across all product categories at Dyson, alongside leading technical specialists and highly motivated creative people to develop products which challenge convention. We are expanding our research capability in Singapore and are currently looking for specialists in machine learning and artificial intelligence specialists to join our team, at all levels.
Work alongside scientists, designers and research engineers to provide analytic insight into Dyson’s research challenges and support to operational issues.
Perform investigatory analysis of large multivariate datasets, identifying opportunities to apply machine learning techniques to extract meaning and derive value.
Optimise analytical workflows by identifying opportunities to increase efficiency and automate processing wherever possible.
Architect the infrastructure and pipelines required for the robust and scalable extraction, transformation, and ingestion of data from a wide variety of data sources.
Collaborate with research engineers to recommend improvements to data collection and experimental strategy to optimise system performance.
Design and develop clean, documented, and easy to maintain code. Integrate software builds with the corporate CI environment where appropriate.
Maximise engagement through understandable data visualisations, effectively and engagingly presenting complex technical information and analysis to senior management.
Awareness of, and full compliance with, data handling and retention regulations.
Master of Science degree in Engineering, Computer Science, or Applied Mathematics; or Bachelor’s degree with experience.
Extensive knowledge of data modelling techniques, and their application to real-world problems.
Practical experience of architecting structured; semi-structured; and unstructured data repositories to optimise their design for anticipated ingestion and access behaviours.
The application of data analysis techniques in a distributed processing environment, e.g. Hadoop, NoSQL, AWS, GCP, would be desirable.
Ability to program in both high and low-level languages as appropriate, e.g. SQL, Java, Python, C or C++.
Enthusiasm to learn and share new methods and techniques.