Reinforcement Learning Engineer

Description

demonstrable mathematical understanding of machine learning, deep learning, and reinforcement learning fundamentals;
​strong Python skills whilst working with TensorFlow and Keras;
hands-on experience in implementing Reinforcement Learning;
experience with developing functioning Deep Q Learning systems;
strong programming skills with proven experience crafting, prototyping, and delivering advanced algorithmic solutions.

Ways to stand out from the crowd

experience with Bayesian Networks;
familiarity with PyTorch or Caffe;
knowledge of optimization algorithms.