Senior Machine Learning Engineer
Starting salary will be based on experience and credentials
San Francisco, California
Dyson is growing - fast. Our ambition is huge. The Senior Machine Learning Engineer will be joining a new and rapidly expanding team at Dyson.
It takes real ingenuity to find new ways of doing things. Smarter technologies. Our Research & Science teams – software developers, engineers and scientists – are the experimenters and risk-takers behind Dyson problem-solving. Whether it’s in-house development, sourcing outside technology partners, or driving collaboration with partner universities, we lead the way in finding the next generation of Dyson technology. Which is why anyone can find themselves presenting to James Dyson himself.
- 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.
- Characterize 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 optimize 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 summarizing 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, where appropriate.
- Master of Science degree or Doctoral degree in Engineering, Computer Science, or Applied Mathematics.
- 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 and Python.
- C and C++ experience is desirable.
- Experience applying machine learning and data science techniques in a distributed processing environment against large quantities of data, e.g. Hadoop, AWS, GCE, TensorFlow.
- Enthusiasm to learn and share new methods and techniques within several areas of technical expertise.