Teams at Peripheral

Support research and engineering experiments in 3D reconstruction, neural rendering, and spatial modeling. Implement and evaluate ML techniques, develop experiment tooling, analyze model outputs, diagnose failures, optimize and integrate promising models into production systems, and document findings. The role requires Python, PyTorch, foundational ML and 3D computer vision knowledge, and in-office work in Toronto without immigration sponsorship.

Conduct a research project in 3D reconstruction, neural rendering, diffusion-based spatial modeling, or world models. Implement and evaluate research techniques, work with captured multi-sensor data, build experiment and evaluation tooling, and clearly present and document findings. Candidates must be enrolled in a relevant degree program, have peer-reviewed publications and strong research experience, and be proficient in Python and deep learning frameworks.

Lead research and development of real-time, photorealistic 3D and 4D reconstruction models for spatial intelligence. Set the research agenda, guide architecture and training strategy, manage datasets and evaluations, and deploy models into production. Lead and grow researchers and infrastructure engineers while evaluating emerging research, contributing to publications and patents, and driving experimentation across multi-node GPU environments.