Job Description
Machine Learning Engineer – Computer Vision / Research / C++ / Python / Object Detection / Depth Estimation. Do you have an MSc or PhD in Computer Science, Machine Learning / Computer Vision? Have a research background and looking for your next contract? Want to join a globally recognized tech company?
If so, then this could be the one for you! We're working with a (household name) tech organization and they need a Machine Learning Engineer to join their team focused on developing solutions for next-gen mobile devices. As a Machine Learning Engineer, you will develop cutting-edge software and algorithms for computer vision, image processing, and deep learning models (amongst numerous other tasks).
This is an inside IR35 contract role based on the Surrey/Greater London border and will require three days per week onsite. Please only apply if you have full working permission in the UK.
Benefits
What's in it for you? You will receive an excellent hourly rate, and hybrid working (3 days per week onsite) whilst working within a diverse, and multicultural team of extremely high caliber individuals.
Requirements
- Masters or higher degree in Computer Science/Engineering, or related disciplines
- 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
Additional Skills
- 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
Application Process
If this sounds interesting and you'd like to learn more, click the link below to apply or email me with a copy of your CV on [email protected]
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