Machine Learning Engineer

  • iGenius
  • Lausanne, VD, Switzerland
  • 04/11/2019
Full time Data Science Data Analytics Big Data Statistics

Job Description

Work somewhere with the creativity of a scaleup and expertise of an enterprise.
We’re looking for an extraordinary Machine Learning Engineer to join our Swiss team.
You’d need a strong computational background (especially in the Machine Learning field), and at least two years of industry experience, as well as world-class team management skills.
If you’re successful, you would:

  • Contribute to machine learning research
  • Formulate and run experiments and improve algorithms based on results
  • Contribute to the company's culture through code reviews
  • Carry out mentoring, research and design discussions
  • Review documents, designs and code done by others and provide constructive feedback
  • Continuously develop your own machine learning and engineering skills, and help others improve theirs
  • Work with ML engineers (also remotely) to migrate research prototypes to production

What You Have

  • Computer Science Bachelor Degree/Statistics/Maths or equivalent
  • Python programming proficiency
  • Experience with Python ML/DL libraries and frameworks (es. scikit-learn, TensorFlow, Keras, Pytorch)
  • Deep learning architectures experience
  • Strong knowledge of designing end-to-end ML flows

Who You Are

  • Able to understand and communicate technical concepts clearly and effectively
  • A collaborative worker, who can enhance performance with a proactive, problem-solving attitude
  • Able to work on multiple projects, under deadline pressure
  • Excellent communicator
  • Fluent English speaker

Working at iGeniusWith a growing team in four offices—Milan, California (San Jose), London and Switzerland —iGenius is a scaleup that thinks like an enterprise, where talented innovators can thrive and people come first. That’s not all.Perks

  • Learning Friday. If our team members know more, so do we. That’s why we give everyone a training budget that they can spend on books, online courses or other training materials
  • Smart Working. Trains can be a drag, so we let our team members work at home when they can
  • Salary is based on experience, and topped up with other bonuses