Machine Learning Engineer - London, United Kingdom - Understanding Recruitment

Understanding Recruitment
Understanding Recruitment
Verified Company
London, United Kingdom

1 week ago

Tom O´Connor

Posted by:

Tom O´Connor

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Description

Machine Learning Engineer - NLP and Computer Vision

Join this disruptive AI company leveraging the best practise in NLP and Computer Vision to help moderate different modes of online content.
As a Machine Learning Engineer you will build world-class models that can effectively understand content and power online safety.

You will work across their domains, designing, deploying and maintaining models which effectively moderate video, text, soundand photo content online.


Their novel approach to AI interprets visual and audio content in context and therefore is ensuring that moderation is accurate and appropriate - evolving the way in which AI is being used to safeguard the internet.


Responsibilities:


  • Design, develop, and maintain cutting edge, robust machine learning algorithms across different modalities
  • Evaluate model performance across different datasets and distribution shifts
  • Investigate possible model failure modes and how they can be solved
  • Keep up to date with machine learning papers and identify relevant research
The role is being offered on either a hybrid or fully remote basis (whichever works for you). There is also excellent training and development on offer - along with a whole host of other benefits.

Keywords:
_ML, AI, Deep Learning, kube flow, argo, knative, AWS, Azure, Google Cloud, GCP, C#, Java, Python, Go, AI, Artificial intelligence, recommendation systems, recommender systems, Python, Machine Learning, Phd, MSc, BSc, computer science, engineer,programmer, developer, NLP, PyTorch, TensorFlow, AWS, GCP, Azure, Cloud, Infrastructure, Development, Developer, Programmer, Programming, Software, AI, Artificial Intelligence, Deep Learning, NLP, Natural Language Processing, Deep Neural Networks, DNN, Scientist,Research, Researcher, Cython, Modelling, Algorithms, Algorithmic, Team Work, Collaboration, Research, GANs, Deep Neural Networks, CNNs, Fairness, Ethics, Research, Scientist, Researcher, PhD, Post Doctoral, Research Fellow, Lecturer, Reinforcement Learning,ACML, NIPS, ICML, ICVPR, Publications, Conferences, Journals, Bayesian Inference, Generative Models_
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