Intern Computer Vision (Toronto)

COMPANY OVERVIEW:

Birdseye’s mission is to help make the world a safer place!

We are the leader in AI-driven Remote Facility Supervision solutions for the Trucking and Logistics Industry. Our Maximum Telepresence Approach™ delivers cutting-edge, data-driven security and operational insights that create a safer working environment for millions of people every year.

We provide end-to-end, cutting-edge hardware and AI-driven solutions, redefining security beyond traditional gatehouses. By empowering our professionally trained monitoring agents, we achieve 99.99% reporting accuracy in mission-critical security, safety, and operational support -24/7/365- for some of the world’s largest logistics facilities, as well as small and medium-sized businesses.

If you're ambitious, thrive in a fast-paced environment, and align with our ICARE values, Birdseye will be the perfect fit for you. If you’re wondering what the world will look like in 10 years - join our Team!

About the Role:

We are looking for an Intern (Computer Vision) to work on real-world perception and AI problems, with an emphasis on modern approaches, experimentation, and turning ideas into practical systems. We are especially interested in M.A.Sc., M.Sc., and Ph.D. students in relevant technical fields. Candidates with a strong portfolio of projects are also encouraged to apply.

What You'll Work On:

Modern computer vision and multimodal AI systems

OCR and visual recognition

Vision-language models and AI agents

Algorithm design and optimization

Confidence estimation and model reliability

Simulation and synthetic data

Active and self-learning systems

Statistical modelling and experimentation

Understanding and improving failure cases in production AI systems

What We're Looking For:

We are looking for someone with a good foundation in modern AI, computer vision, algorithms, mathematics, or statistics, and an interest in learning and solving practical problems.

Designing algorithms and reasoning through technical problems

Understanding modern AI architectures and research

Breaking down open-ended problems into testable ideas

Designing and running experiments

Working with real-world datasets

Reading research papers and applying relevant ideas

Analyzing why AI systems fail

Building and testing ideas independently

Who Should Apply:

We care more about what you have worked on and how you approach problems than your title or degree. Graduate students are ideal, but undergraduates and self-taught candidates with a strong portfolio of AI/CV work are also encouraged to apply.

-To apply: Please include your resume/CV, portfolio or GitHub, and 1-3 projects or research efforts you are particularly proud of.

This role will require the candidate to complete background checks (includes but not limited to: references, educational verification, criminal check, credit check - where applicable). Certain roles may also require testing.

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