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XYZ Reality

Engineering-grade AR with real-time project controls

Senior AI / Computer Vision Engineer

Computer VisionUpdated on Nov 10
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • At least 5 years of industrial experience in computer vision, including hands-on experience solving complex technical problems.
  • An MSc or PhD in Computer Vision, AI, Computer Science, or a related discipline.
  • Deep expertise in 3D computer vision and spatial AI.
  • A 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, explore emerging techniques, and build robust, deployable products.
  • Strong debugging and problem-solving skills and ability to work through complex, ambiguous technical challenges.
  • Ability to work effectively across multidisciplinary engineering teams.

Responsibilities

  • 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 that understand 3D environments, spatial relationships, and physical geometry.
  • Develop automated building information modeling (BIM) correspondence and object-matching capabilities.
  • Develop algorithms using multimodal sensor data.
  • Combine AI, 3D vision, simultaneous localization and mapping (SLAM), and BIM to develop geometric and spatial reasoning capabilities.
  • Explore emerging scene representation techniques, including Gaussian Splatting and neural radiance fields (NeRFs).
  • Improve localization-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.
  • Optimize models for embedded deployment, improving inference speed, accuracy, and robustness.
  • Deploy and optimize models for embedded GPU platforms.
  • Build and improve production inference pipelines, benchmarking performance, latency, and accuracy.
  • Contribute to technical architecture, design reviews, and technical direction.
  • Share knowledge and mentor other engineers.

Desired Qualifications

  • Experience with perception for autonomous or embodied systems, such as SLAM, sensor fusion, or state estimation.

About the Company

XYZ Reality

Engineering-grade AR with real-time project controls

XYZ Reality delivers real-time project controls using engineering-grade augmented reality to help construction teams manage complex projects on time and within budget. Its product overlays precise, on-site information through augmented reality, giving workers real-time field data to track progress, monitor quality, and identify issues before they cause delays. Real-time data and AR guidance enable proactive problem solving and faster decision making, reducing risk and waste. The company differentiates itself with engineering-grade AR that provides exact, objective field measurements and visibility, backed by experience managing over $12 billion in mission-critical projects and partnering with leading developers. Its ultimate goal is to help construction teams deliver projects faster, with lower costs and higher quality, while supporting sustainability and quicker revenue generation.

Company size
201-500
Company stage
Grant
Total funding
$35.4M
Headquarters
London, United Kingdom
Founded
2017

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