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- Have technical responsibility for one or more significant sections of the assigned project
- Translate complex functional and technical requirements into detailed design
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- Professional software development experience with C++ and Python
- Experience developing with machine learning frameworks – Tensorflow/Pytorch
- Expertise in image-based 3D reconstruction: Photogrammetry, Neural Radiance Fields (NERF) or Gaussian Splatting techniques.
- Programming proficiency one or more of programming language and APIs like C++/Java/Python
- Excellent communication, teamwork and a results-oriented attitude
- Proficiency in problem-solving and debugging
- Experience in Generative AI, including hands-on implementation of state-of-the-art models.
- Computational photography, image inpainting and 3-D vision
- Model optimization and knowledge distillation.
- Experience in computer graphics and rendering: design and development of software such as OpenGL, OpenGL ES, Vulkan or DirectX
- Experience in Android application development
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Machine Learning Engineer - Staines-upon-Thames, United Kingdom - SAMSUNG
Description
Position Summary
The AI team at Samsung Research UK is currently looking for Computer Vision and Machine Learning Engineer to join our team in Staines-upon-Thames. This is a good opportunity to work on next-generation mobile devices from Samsung.As a forward-thinking company, we are at the forefront of innovation and seek an individual with a passion for pushing the boundaries of AI and content creation, and processing of live camera frames and images on PC and mobile environment. The prospective engineer will have an opportunity to work in production environments and solve industry-relevant problems.
This role is available on a 6 month contract basis. We operate a hybrid model of 3 days onsite and 2 days working from home weekly.
Role and Responsibilities
As a Machine Learning Engineer, you will:
Skills and Qualifications
Essential Skills
Desirable Skills
Contract Type: 6 Month Contract (inside IR35)
Location: Staines-upon-Thames, Surrey, UK
Hybrid Policy: 3 days a week onsite and 2 days working from home if preferred
