Senior AI - Computer Vision Engineer - UK
Xyz Reality
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114 open computer roles across 62 companies are on ApplySarthi right now, most of them in Delhi NCR (5), Bengaluru (5), Chandigarh (1).
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What computer roles keep asking for: Python (60%), Computer vision (57%), Machine learning (39%), C++ (39%), PyTorch (29%), Deep learning (28%), Git (16%), Linux (16%) — counted across their open postings here.
Computer vision jobs · Deep learning jobs · Machine learning jobs · PyTorch jobs
Xyz Reality has 12 open roles listed here.
- Customer Success Manager
- Talent Acquisition Partner, Generalist
- Production Assembly & Test Engineer
- ERP Administrator (Odoo)
- Enterprise Account Executive - Construction
Counted across 14 company job boards, updated as roles open and close.
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- Why do you want to join Xyz Reality?
- What is your experience with Computer vision? Tell me one thing you learned the hard way.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
- How would you explain your model's result to someone who is not technical?
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Practise the Senior AI - Computer Vision Engineer - UK at Xyz Reality interview free →Senior AI / Computer Vision Engineer Build the spatial AI behind the future of construction At XYZ Reality , we've created the world's first engineering-grade Augmented Reality solution for construction. Our technology, The Atom, is already being used on major construction projects around the world to help teams build more accurately, efficiently and with fewer mistakes. Our R&D team applies computer vision, spatial AI and machine learning to one of the most demanding real-world settings there is: the active construction site. We’re looking for a Senior AI / Computer Vision Engineer with deep expertise in 3D computer vision and spatial AI to join the team and help develop the perception technology behind our products. As a Series B business entering our next phase of growth, we're investing in our R&D capability and growing our team. This great opportunity will be based out of our Angel, London office on a hybrid basis, 2-3 days per week. The Role This is an opportunity to solve computer vision problems that exist at the intersection of the digital and physical world. You’ll develop the perception and scene-understanding systems that enable our wearable technology to recognise construction objects, understand complex 3D environments, and relate what’s on site to the design model, using real-world sensor data. For this role, 3D / spatial computer vision expertise is fundamental. We’re looking for someone who understands how AI and computer vision can reason about physical space, not simply someone with broader AI or machine learning experience. You’ll work across research, algorithm development, optimisation, deployment and productisation, taking sophisticated computer vision techniques and turning them into robust technology capable of performing on active construction sites. You’ll bring senior technical expertise to the team as we build our capability and presence in Calgary. You’ll also collaborate closely with our Navigation, Embedded Software, Hardware and Product teams across the wider business. This is a role where you can combine deep technical work with real-world impact, seeing the algorithms and systems you develop ultimately deployed through wearable technology on some of the world's most complex construction projects. What You’ll Be Doing Develop advanced computer vision algorithms for construction scene understanding and spatial intelligence. Design and develop semantic segmentation, object detection and instance segmentation models. Build algorithms capable of understanding 3D environments, spatial relationships and physical geometry. Develop automated BIM correspondence and object-matching capabilities. Develop algorithms using multi-modal sensor data. Combine AI, 3D vision, SLAM and BIM to develop geometric and spatial reasoning capabilities. Explore emerging scene representation techniques including Gaussian Splatting and NeRFs. Improve localisation-assisted perception and robustness across varying lighting, weather and real-world site conditions. Design, train and evaluate large-scale deep learning models. Develop data pipelines supporting supervised, self-supervised and semi-supervised learning. Evaluate emerging foundation models, multimodal AI and modern computer vision techniques where they can add meaningful value. Optimise models for embedded deployment, improving inference speed, accuracy and robustness. Deploy and optimise models for embedded GPU platforms. Build and improve production inference pipelines, benchmarking performance, latency and accuracy. Contribute to technical architecture, design reviews and our technical direction. Share knowledge and mentor other engineers as the team continues to grow. What We’re Looking For 5+ years’ industrial experience in Computer Vision, with strong hands-on experience solving complex technical problems. MSc or PhD in Computer Vision, AI, Computer Science or a related discipline. Experience with perception for autonomous or embodied systems, such as SLAM, sensor fusion or state estimation, would be valuable. Deep expertise in 3D Computer Vision / Spatial AI, this is a core requirement for the role. Strong understanding of geometry, spatial relationships and scene understanding. Experience developing and deploying computer vision and deep learning systems in production. Strong Python development skills and expert knowledge of PyTorch. Experience with semantic segmentation, object detection, image understanding and modern computer vision architectures. Experience designing and training large-scale deep learning models and working with large image datasets. Strong mathematical foundations in machine learning and computer vision. Ability to bridge research and production engineering, comfortable exploring emerging techniques while remaining focused on building robust, deployable products. Strong debugging and problem-solving skills and the ability to work through complex, ambiguous technical challenges. A collaborative approach and the ability to work effectively across multidisciplinary engineering teams. What matters most for this role is genuine depth in 3D / spatial computer vision and the ability to apply that expertise to complex, real-world engineering problems. We’re particularly interested in someone who is curious about where computer vision and AI are heading, but who also has the practical engineering mindset to turn emerging research into technology that works reliably outside of the lab. What You Could Be Working On From the outset, you’ll have the opportunity to contribute to some of our highest-priority R&D initiatives, including: 3D construction scene understanding Construction semantic segmentation Automated BIM understanding and object correspondence Spatial reasoning across wearable sensor data Embedded AI deployment Foundation models for construction understanding Perception for wearable AR Why Join Us 🚀 Work at the intersection of Spatial AI, 3D Computer Vision, AR and real-world engineering 🧠 Solve genuinely difficult perception and scene-understanding problems 🥽 Develop AI that ultimately runs through physical, wearable technology – not just software on a screen 🏗️ See your work applied to some of the world’s most ambitious construction projects 📈 Join a Series B business at an exciting stage of international growth 🔬 Work alongside specialists across Computer Vision, AI, Navigation, Embedded Software and Hardware 💡 Have meaningful influence over technical architecture and the future direction of our perception technology 🌍 Build technology with tangible, real-world impact If you’re passionate about 3D computer vision and spatial AI, enjoy solving difficult problems at the intersection of research and engineering, and want to see your work move from algorithms into technology being used in the physical world, we’d love to hear from you. 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Listed on arbeitnow · posted 2026-11-01. ApplySarthi collects openings and links to application pages; the role is advertised by Xyz Reality, not by us.