Computer Vision / Machine Learning Guru
Top PhD / MSc, Visual Geometry, Deep Learning
£Outstanding + shares (likely to be over £70k for the right experience)
Can you offer an outstanding academic record in Advanced Visual Geometry and Machine / Deep Learning as applied to Computer Vision? This is a very rare opportunity to join a renowned and highly respected team working on leading edge research encompassing Computer Vision, Machine Learning, Artificial Intelligence, Neural Networks, Planning Systems, Robotics and 3D Mapping.
You will earn an outstanding salary - but also acquire start-up stock options in a future global leader!
Only the best need apply: These exciting roles call for exceptionally bright researchers who are self-starting high-achievers – with very strong mathematics skills and proven coding fluency (for example C / C++, Python, Scala, MATLAB, Java). You should of course also have an outstanding academic background (PhD / Masters from a top University & publications in top scientific journals) plus proven postgrad / industrial research experience, along with the drive and ambition to rapidly advance your career.
The role calls for:
- Strong analytical background and deep understanding of large-scale optimization, numerical linear algebra, probabilistic inference
- Strong programming skills (Python, C/C++, Scala, Matlab, Java), experience with computer vision and deep learning packages (OpenCV, TensorFlow, Caffe, Torch, Theano, MatConvNet), GPU programming including CUDA
- Excellent communication skills (fluency in English essential)
- Desire to work in a fast-paced start-up environment
Your responsibilities will include:
- Develop state-of-the-art large scene understanding capability based on algorithms for processing multi-modal sensory data, including vision, LIDAR, radar, audio and IMUs and implement them, for example in CUDA-based GPUs
- Research effective and computationally tractable means to deliver accurate pixel-level labelling of objects in scenes, drawing on techniques such as simultaneous location and mapping (SLAM), convolutional neural networks (CNNs) and conditional random fields (CRFs)
- Research techniques for training and optimising algorithms to improve perception system accuracy and reliability, especially in relation to semantic segmentation, object recognition, object segmentation, object state, depth and gesture recognition and propose computationally tractable solutions for engineering implementation
- Research appropriate techniques, including autonomous agents, for developing 3D simulation environments capable of generating synthetically-labelled training data for CNNs, for replaying real-world test cases and for directed random test generation to deliver validation coverage for the Five AI stack
- Design, implement, test highly-efficient algorithms for estimating object tracking and prediction
- Generate novel research techniques for solving multiple challenges in the field of computer vision as applied to autonomous vehicles and work to get outputs published in the world’s top scientific journals and conferences
As the team grows, you will find yourself quickly surrounded by subject matter experts in one of the most exciting technology domains and will rapidly gain knowledge and experience.
Please note: even if you don’t have exactly the background indicated, do contact us now if this type of job is of interest – we may well have similar opportunities that you would be suited to. And of course, we always get your permission before submitting your CV to a company.