Peripheral is developing spatial intelligence, starting in live sports and entertainment. Our models generate spatial data, used for advanced sports analytics and immersive media experiences. We’re solving key research challenges in 3D computer vision, creating the foundations for the next generation of robotic perception and embodied intelligence.

Our team includes engineers and researchers from leading technology companies and research institutions, and we’re building technology at the intersection of AI, graphics, and the future of live entertainment. We're seeking a Reconstruction Engineer to join Peripheral's Reconstruction team, helping push the state of the art in 3D reconstruction, neural rendering, and spatial models (monocular depth estimation, multi-view stereo, and beyond). You'll report to our Senior Reconstruction Engineer and work primarily on the research side of the team, developing and evaluating recent approaches, with exposure to how the most promising results make their way into Peripheral's core pipeline.

You've done research in 3D reconstruction, neural rendering, or related spatial modeling problems, and you have the publication record to show for it. You're comfortable going from a new idea or paper to a working implementation and an honest evaluation of whether it holds up.

You think carefully about the full spectrum of spatial understanding, from classical multi-view geometry to neural approaches like NeRFs and Gaussian splatting, and you have your own opinions about where the field is headed.

You're excited by the opportunity to help shape Peripheral's research culture from an early stage: the standards, rigor, and ways of working you help establish now are what the team will build on as it grows.

Design, run,



and analyze experiments across 3D reconstruction, neural rendering, and spatial models (monocular depth estimation, multi-view stereo, NeRF/Gaussian-splatting-style approaches, etc.).

Implement and evaluate new techniques from the research literature and from your own ideas, and report results clearly to the team.

Help move promising research into production by profiling, optimizing, and handing off models in a form the rest of the team can build on.

Master's or PhD in Computer Science, Robotics, Computer Vision, or a related field.

CVPR, ICCV, ECCV, NeurIPS, 3DV) in 3D reconstruction, neural rendering, or spatial modeling, as a first author or major contributor.

Strong research experience in 3D reconstruction and spatial modeling, across both classical (multi-view geometry, structure-from-motion) and neural (implicit representations, neural rendering) approaches.

Proficiency in Python and a deep learning framework, with a track record of implementing and training models from scratch.

Candidates must have the legal right to work in Canada and be willing to relocate to Toronto for an in-office role. At this time, we are unable to provide immigration sponsorship.

Experience with SLAM frameworks, point cloud processing, or 3D reconstruction libraries (e.g., COLMAP, Open3D, PCL).

Experience with large-scale spatial data pipelines (multi-camera/LiDAR capture, calibration).

Background in robotics, autonomous systems, or motion capture applications of 3D reconstruction.

Competitive equity package as an early team member.

Annual salary of $100K-$150K CAD plus performance bonuses, commensurate with experience.

Full ownership of high-impact projects shaping the future of spatial intelligence and 3D media.

Flexible Paid Time Off (PTO).

Comprehensive health, dental, vision, and wellness benefits.

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📌 Machine Learning Engineer - PhD in Machine Learning (Toronto)
🏢 Dover
📍 Toronto