Machine Learner – UnifyID – Redwood, CA

About the Role
We are looking for a math+code engineer/signal-processor/hacker/self-proclaimed individual who is comfortable with crafting, hacking, implementing, re-implementing and most importantly, breaking Machine Learning algorithms deep, shallow, or otherwise.

If you think you have the answers/(mis-)informed opinions on one or more of the following questions, we’d like to hear from you! (a.k.a. you’ll love it here!)

  1. The great generative model wars [GANs vs Pixel-RNNs vs VAEs]: Who do you think will win and why?
  2. Word on the Kaggle street is that XGBoost is killing it! Why do you think this is?
  3. Do you think that the problem of counting independent sets in a bipartite graph is not #P-complete but #BIS? Why so?

As language/platform agnostic as we are (we use Lua, Python, Julia and R on a daily basis and are eagerly awaiting the Milk compiler from the CSAIL folks too), we expect you to be unreasonably good at and evangelize at least one of the tuples in the Cartesian product of L X P X O where L={Python, Scala, Julia, R, Lua, C++, Java}, P={Scikit-learn, Torch/Autograd, Caffe, Keras with Theano/TensorFlow, Chainer}, and O={Ubuntu, OS X, RHEL / CentOS / Fedora} and pick things up when required.

First application date:


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