Senior Deep Learning Research Engineer

Requirements

• If you are motivated by the challenge of applying cutting-edge Deep Learning in messy, real-world environments where your input directly reduces the global carbon footprint, you are in the right place
• 3+ years (5+ preferred) applying deep learning in industry settings
• Experience with applying latest Deep Learning research in PyTorch
• Experience with active learning, semi-supervised learning, learning from noisy labels, model robustness (at least two)
• Experience with architectures such as YOLO, ViT, ResNet
• Ability to write clear, efficient, and scalable code using Python and PyTorch
• Experience with numpy, scipy, OpenCV, Albumentations
• Analytical detail-oriented mindset with strong abstract thinking and a solid theoretical understanding of neural networks
• (Desirable) Experience in the waste industry
• (Desirable) Startup or scale up experience

What the job involves

• You will report directly to the Head of Deep Learning
• You will work within a focused DL team and collaborate with a dedicated Data team
• You will also regularly interact with the wider company to ensure technical alignment across the organisation
• If you live in London or within commuting distance, we’d like you to come into the office at least once a week. If you’re elsewhere in the UK, we ask you to come in once a month, and for our Quarterly All Hands
• As a Senior Deep Learning Research Engineer, you are an architect of a sustainable future. You will have the autonomy to propose, discuss, and implement the best solutions for our customers
• Pushing the boundaries of deep learning by building upon the latest research in object detection and classification
• Developing deep learning methods using best software development practices; training, analyzing, and reporting model performance
• Developing internal tools to further automate research and analysis workflows

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