Deep Learning Engineer, V7 Labs

• Experience in deep learning, from understanding the underlying math, to the ability to illustrate landmark papers within the vision domain (given enough prep time)
• Evidence of individual contribution to challenging DL/ML projects
• A CV that demonstrates an early interest in computer science
• A curious, scientific mind
• Fluent in English

• General purpose models
• Instance and semantic segmentation (centroid approaches, high-fidelity semantic segmentation for labelling)
• Multi-task models (eg. Taskonomy and related papers)
• Auto-ML in vision
• Ultra-large model backbones (eg. MOCO and related papers)
• We're based on PyTorch, our BE is in Elixir (erlang), and FE is Vue.js. We make GPU machines available both at our office or in the cloud. We are regular CVPR/NeurIPS/ECCV attendees and in normal times attend as a team
• An inference and training orchestration engine to run any model request in real-time across a library of computer vision models
• Several implementations of instance-segmentation architectures like Mask-Rcnn, CenterMask, and object detection architectures like VoVnet
• Configuration parameters to enable the training of models across various dataset sizes, image sizes, and relative annotation sizes and amounts
• The development of deep image retrieval systems to automatically rank datasets by content-based parameters without the need of prior training

• Top 15% quartile equity options plan through an EMI scheme
• Private Healthcare via Vitality
• Learning and Development wallet of £800 per year
• Monthly well being and mental health budget
• Personalised benefits platform via Thanks Ben
• Enhanced parental leave
• 25 days paid holiday with unlimited additional days
• 4-day company-wide and 4 day departmental retreats in stunning locations
• Visit London to meet us in our HQ. We have a barista & plenty of snacks
• Hybrid working with flexibility or remote working
• Temporary work from anywhere for one month in the calendar year
• Paid tickets, accommodation, and travel to relevant conferences, nationally or internationally (NeurIPS, ICCV, CVPR, ...) to expand your network & knowledge during normal times
• Apple hardware provided plus a £500 budget from home office equipment

Total funding: $50m

AI is currently utilised across multiple industries, requiring companies to continuously collect, organise and label image data so that AI models will be able to adapt to new scenarios. V7 Labs is a computer vision platform that helps AI teams develop vision-based models that are learning continuously from training data with minimal human supervision.