Please note that this vacancy has expired and you can no longer apply.
if you are a self-starting high-energy engineer, computer scientist, mathematician or physical scientist and want to play your part in shaping the future, come and join us.You’ll be responsible for designing and building both supervised and unsupervised learning technologies to parse objects and determine their state as far as it is relevant to driving decisions. States might include object classifications, traffic signal states, orientations, wheel angles and human actions.
You’ll have practical experience of using machine learning and it would be advantageous, but not essential, for this to be in the field of convolutional neural networks for computer vision. We’d also expect you to be familiar with some of the techniques for unsupervised learning. In any case, you’ll have a good working knowledge of at least one widely available ML toolkit, such as Theano, Caffe, Tensor Flow or Torch.
You’ll have proven software development experience using C/C++, Python, Scala or Java. You’ll be familiar with OpenCV.
You’ll have a 1st or upper 2nd class degree, or equivalent, in computer science, mathematics, engineering or physical sciences, with a strong mathematics content, from a top university.
Experience from the automotive or computer gaming industries and familiarity with open source development platforms, such as Linux and Git, would be assets.
Join a European leader bringing autonomous vehicles to market and feel like there is a part of you ‘on the car’
Benefit from working closely with our founders who have previously built and run successful tech companies through to exit
Have immediate impact on a smart, growing, low-ego multi-cultural team
Grow with us as we scale up whilst delivering meaningful work that really matters
Enjoy a competitive salary package, BUPA medical care and stock options
FiveAI is committed to Equal Employment Opportunity through attracting and retaining a complementary team of employees and building an inclusive environment for all.
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Apply for: Machine Learning for Visual Scene Understanding