ML Engineering Intern: 3D Vision in Production & Cloud

Socket.dev; Toronto; On-site; CAD 20,000 - 27,000; Full time

Job summary

Peripheral is seeking an ML Engineering Intern to join our motion capture team. You will help deploy, maintain, and improve markerless pose estimation systems that process multiview video in real time.

Focus areas include cloud deployment, data curation, and iterative model improvements for production readiness. The internship lasts 12 months, starting Fall 2026 and ending Fall 2027, with in-office work based in Toronto.

Qualifications

• Pursuing Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field.
• Strong foundation in 3D computer vision fundamentals, including camera calibration, multi-view geometry, and 3D coordinate transforms.
• Proficiency in Python and familiarity with a common deep learning framework.
• Candidates must have the legal right to work in Canada for the duration of the internship and be based in or willing to relocate to Toronto for an in-office role.

Responsibilities

• Deploy and maintain pose estimation models in cloud infrastructure, focusing on containerization and deployment pipelines.
• Curate, clean, and analyze training data to identify gaps or quality issues.
• Experiment with model improvements and evaluate results against real-world accuracy.
• Use evaluation tools to diagnose failure modes and prioritize fixes.
• Collaborate with the motion capture team to understand camera setup, calibration, and data pipeline effects on model performance.
• Document work and contribute to data and deployment tooling.

Skills

3D vision

Python

Deep learning

Data quality

Education

CS/EE/Robotics degree

Tools

Docker

Kubernetes

AWS

GCP

Job description

Peripheral is seeking an ML Engineering Intern to join our motion capture team. You will help deploy, maintain, and improve markerless pose estimation systems that process multiview video in real time.

Focus areas include cloud deployment, data curation, and iterative model improvements for production readiness. The internship lasts 12 months, starting Fall 2026 and ending Fall 2027, with in-office work based in Toronto.