Machine Learning Intern
Thames, United Kingdom, Upon, Communications House,, Staines
3d ago

Position Summary

Start date : As soon as possible

Duration : 6 Months (some flexibility)

Role and Responsibilities

Samsung is the world’s leading manufacturer of TV products, and at SRUK we are continually pushing the boundaries of technology to develop innovative and exciting features for our customers.

The DTV team at SRUK is looking for an exceptional intern to join our team in Staines-upon-Thames. The team undertakes projects involving the application of cutting-edge academic research into proof-of-concept and commercial products for Samsung TV devices.

The prospective candidate will have the opportunity to contribute to the development and optimisation of models and ML frameworks for the next generation of Samsung TV devices.

This is an exciting opportunity to work on some of Samsung’s most advanced products before they are launched. You will be a part of a dynamic research lab working with experts in DTV and AI.

Interns at Samsung Research UK are encouraged to write high quality research papers and / or contribute to patents towards the end of their internship.

Skills and Qualifications

Required Skills

Master’s level degree or a doctorate in Computer Science or a related subject

Excellent knowledge of machine learning and computer vision fundamentals, and deep-learning concepts such as CNNs, RNNs / LSTMs, Deep Reinforcement learning, Multi-task Learning.

Excellent knowledge of linear algebra, probability and statistics.

Programming experience in Python and / or C / C++.

Programming skills in deep learning and computer vision frameworks, such as PyTorch, TensorFlow, Caffe, Torch and OpenCV.

Experience with computer vision algorithms and tasks such as object detection and pose estimation.

Desirable Skills

Experience with deployment of machine learning methods for mobile and edge devices.

Experience with automated machine learning methods such as neural architecture search (NAS), architecture design, hyper-parameter optimisation, model compression and selection.

Publications in top AI conferences (e.g. AAAI, ICML, ICCV, CVPR, NeurIPS, SysML or similar).

Contribution to open source deep learning and computer vision frameworks such as TensorFlow, TensorFlow Lite, OpenCV etc.

Experience with image and video processing algorithms such as image filtering and compression.

Experience with constrained and numerical optimisation methods.

Understanding of performance optimisation for devices with limited resources

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