We are looking for a talented and creative Machine Learning Engineer / Data Scientist, with a passion for algorithms development and data science, who can contribute on challenging R&D projects and deliver consistent high-quality work.
The successful candidate will be continuing development of physiological sensor data based sleep and relaxation staging algorithms (across a variety of products) as well as looking for data insights around audio content usage.
This is an excellent opportunity to apply and develop your technical and scientific skills in a variety of areas; developing new algorithms, signal processing, looking for insights in big data sets, developing future neuro-audio based consumer product systems and joining an experienced and ambitious product development team.
Kokoon Tech is an award winning, venture capital backed, health and wellness start-up based in London helping the world relax and sleep easier through audio & data. Their app-based software and sensor-enabled products provide adaptive audio content and coaching clinically shown to induce and protect relaxation. After shipping their first headphone product in 2018 they have sold over 20,000 units to over 50 countries (see kokoon.io)
- Good Degree in Computer Science/Mathematics/Physics or a related field
- Excellent software engineering skills (Python/MATLAB or other equivalent)
- Strong interest in Machine Learning, Data Science, Signal Processing
- Excellent communication and teamwork skills
Desirable skills include
- Professional software engineering experience
- Professional experience deploying Machine Learning in production
- MSc/PhD in Machine Learning/Statistics or a related field
- Familiarity with Python Machine Learning stack: numpy/pandas/scikit-Learn
- Experience working in a startup
- Laboratory/Practical experimentation experience
- Recommender Systems
- Generous share option
- Competitive salary
- Pension scheme
- 25 days holiday (+ bank holidays)
- Friendly/dynamic team (come meet us!)
- Work-from-home days
Will involve a (supervised) machine learning exercise based on the work we undertake.