Machine Learning Engineer - Deep Learning/ NLP

Job Description

• Machine Learning Engineer - Deep Learning/NLP (5-10 yrs) - Please note we are also considering Phd Mathematics candidates for Machine Learning as this profile is 80% to 90% research & algorithms. If you : a) Are familiar with traditional areas of NLP such as topic-modelling and sentiment classification b) Have made the move to deep learning architectures c) Want to understand the intricacies of machine-based classification and summarization of content question-answering and language correction (any experience in these areas will be regarded as a plus) - We are interested in talking to you for a Machine Learning Engineer or Machine Learning Researcher position. The ideal candidate would : a) Have experience in and knowledge of deep learning frameworks. We work in Tensorflow and Keras but knowledge of other frameworks will be considered equivalent. We expect that a functional knowledge of Python is a given. b) Have some experience in deep-learning methodologies. Experience in other areas of deep-learning such as computer vision or time-series prediction will be considered equivalent. However we do expect you to have the drive to adapt and expand your knowledge for use in the domain of Natural Language Understanding. c) Have a great understanding of the fundamental mathematics that underlies deep learning. Brush up on your linear algebra derivate calculus and probability theory. d) Have some programming experience in enterprise setups. Being part of a larger pipeline we build and deliver to a spec; so we will expect moderate-to-advanced programming chops. e) Any research publications or Degrees in the fields of Mathematics and/or Deep Learning will be a definite advantage. If you dont fit this set of requirements but are a great programmer with strong fundamentals in data structures cloud-based services and NoSQL databases and are looking to get started with Deep Learning we still want to hear from you! As an individual you should : a) Be self-driven and need very little to no supervision b) Be willing to understand the trade-off between research and enterprise-style work c) Be willing to engage with other members of your team share your knowledge and learn from everyone else. This is important

Job Summary