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Machine Learning Engineer - Deep Learning, start up, genomics

Posted 9 March by Ability Resourcing Easy Apply Ended

Challenging opportunity for a Machine Learning Engineer looking to make an impact in an early stage start up building the world's first intelligent genomics platform that understands DNA data. The company is offering researchers and corresponding organisations a highly scalable system that automates the analysis process and learns from very sensitive datasets to derive meaningful insights.

As one of the first Machine Learning Engineers you will work with complex genetic data sets, using state of the art machine learning and deep learning methods performing both exploratory and targeted algorithms research and development with large scale data.

You will work with a high-impact team with many years of experience in science, software engineering and web development, that are passionate about making a difference in the healthcare industry.

The ideal candidate will come from a statistical, machine learning or data science background, and have experience with relevant research in Natural Language Processing, reinforcement learning, active learning and/or probabilistic Bayesian leaning.

The Machine Learning Engineer is a research-minded individual with a good software development background having worked with, for example, Python and C++ and has an understanding and interest in Deep Learning (using frameworks such as Pytorch/Tensorflow).

Within this dynamic small team environment you will be pushing the boundary of fundamental knowledge and turning it into products people love.

We are looking for someone that thrives in a fast-paced start up environment, is interested in working with a close-knit team and is intrigued by dealing with sensitive and complex data sets.

Start up, Machine Learning, Deep Learning, NLP, reinforcement learning, Bayesian Learning, Python, C++, genomics, Tensorflow, Pytorch

Required skills

  • C++
  • Machine Learning
  • Python
  • NLP
  • Start up
  • genomics
  • Deep Learning
  • Tensorflow
  • Pytorch
  • reinforcement learning
  • Bayesian Learning

Reference: 34647158

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