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Lead Machine Learning Engineer at Dyson

Description


The Machine Learning team is responsible for delivering tangibly intelligent devices across all current, and future, product categories at Dyson.

Working alongside researchers, engineers, and designers, we blend cutting-edge machine learning and artificial intelligence techniques with an in-depth understanding of user behaviours. We utilise anonymised data from our connected devices and build prototype rigs to conduct rigorous qualitative and quantitative experiments and trials, inventing novel solutions to 'impossible' problems.

You will play a pivotal role in a rapidly growing team, developing intelligent features for our existing product categories, or enabling core functionality in products that most can’t even imagine.




Accountabilities

  • 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, suggesting novel techniques for data collection during future experiments and field trials.
  • Identify opportunities to apply machine learning techniques to extract meaning and derive value.
  • Characterise classifier or algorithm performance against defined project objectives; proposed implementation environment; and associated computational constraints.
  • Collaborate with research engineers to recommend improvements to data collection and experimental strategy to optimise system performance.
  •  Application of statistical methods to establish confidence in findings.
  • Design and develop clean, documented, and easy to maintain code. Integrate software builds with the corporate CI environment where appropriate.
  • Produce reports and presentations summarising progress against team and project goals, effectively and engagingly presenting complex technical information and analysis to senior management.
  • Work independently to manage tasks with competing priorities.
  • Collaborate with academic and industrial partnerships to leverage externally available expertise.
  • Generation of novel intellectual property.



Skills

  • Doctoral degree or Master of Science degree in Engineering, Computer Science, or Applied Mathematics; or Bachelor’s degree with significant experience.
  • Expert knowledge of machine learning algorithm development and implementation in complex systems including hardware, software application and cloud-based components.
  • Demonstrable machine learning or data science experience with a proven track record outside of academia, ideally working with Agile development methodologies.
  • Feature extraction, time series analysis, signal processing, and statistical modelling.
  • Ability to program in both high and low-level languages as appropriate, including Java, Python, C, C++ and in Matlab.
  • techniques against real-world problems would be desirable.
  • Enthusiasm to learn and share new methods and techniques within several areas of technical expertise.
  • Passionate about the technical and personal development of junior team members.

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