ML Engineer - Reconstruction

Reposted 5 Hours Ago
Toronto, ON, CAN
In-Office
100K-150K Annually
Entry level
Artificial Intelligence • Computer Vision • Digital Media • Sports
The Role
Develop and evaluate research approaches for 3D reconstruction, neural rendering, and spatial modeling. Implement techniques from research literature, run rigorous experiments, analyze results, and help transition promising models into production through profiling and optimization. The role focuses on classical and neural computer vision methods, including multi-view geometry, monocular depth estimation, NeRFs, and Gaussian splatting.
Summary Generated by Built In

WHO WE ARE:

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.

We’re backed by top investors, including Khosla Ventures, Inovia, Deloitte Ventures, Daybreak, and Entrepreneurs First, and working with some of the biggest names in sports. 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 ambitious and looking to win.

THE OPPORTUNITY:

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 new approaches, with exposure to how the most promising results make their way into Peripheral's core pipeline.

This is a role for someone who has already done serious research in this space and wants to see their work move beyond the paper: someone who can run rigorous experiments independently, while learning what it takes to turn a strong result into something reliable enough to run at scale.

WHO YOU ARE:

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 work independently and take ownership of your experiments, but you're also a strong collaborator: you share results openly, welcome feedback, and learn quickly from the people around you.

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.

WHAT YOU'LL BE DOING:

  • 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.

REQUIREMENTS:

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

  • Publication(s) at a top-tier venue (e.g., 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.

  • Strong communication skills, able to explain results and trade-offs clearly to both researchers and engineers.

  • 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.

NICE TO HAVE:

  • 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).

  • Open-source contributions or released code and datasets associated with your research.

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

WHY YOU’LL LOVE WORKING HERE

  • Competitive equity package as an early team member.

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

  • Unparalleled access to premier global sporting events and iconic venues.

  • 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.

Skills Required

  • Master’s or PhD in Computer Science, Robotics, Computer Vision, or a related field
  • Publication at a top-tier venue such as CVPR, ICCV, ECCV, NeurIPS, or 3DV, as a first author or major contributor
  • Strong research experience in 3D reconstruction and spatial modeling, including multi-view geometry, structure-from-motion, implicit representations, and neural rendering
  • Proficiency in Python and a deep learning framework, with experience implementing and training models from scratch
  • Strong communication skills and ability to explain results and trade-offs to researchers and engineers
  • Legal right to work in Canada
  • Willingness to relocate to Toronto for an in-office role
  • Experience with SLAM frameworks, point cloud processing, or 3D reconstruction libraries such as COLMAP, Open3D, or PCL
  • Experience with large-scale spatial data pipelines, multi-camera or LiDAR capture, and calibration
  • Open-source contributions or released research code and datasets
  • Background in robotics, autonomous systems, or motion capture applications of 3D reconstruction
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The Company
16 Employees
Year Founded: 2024

What We Do

Peripheral is a Toronto-based AI research lab building spatial intelligence for live sports and entertainment. It uses robotics-grade perception, multi-camera systems, and advanced 3D reconstruction to turn live events into real-time, photorealistic, navigable environments. Its platform supports interactive browser-based replays, immersive fan experiences, and high-fidelity player and ball tracking, while also advancing applications in officiating, injury prevention, and embodied intelligence.

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