Intern AI Systems (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 (AI Systems) to help design and build agent-based systems that can reason, use tools, evaluate outcomes, and improve through feedback. 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:

• Designing single-agent and multi-agent systems
• Building tool-use and function-calling workflows
  
• Designing feedback loops for agents to evaluate and improve their outputs
• Agent planning, memory, delegation, and coordination
• Building evaluation frameworks for agent performance
• Designing systems where agents interact with software, data, and other AI models
• Developing autonomous workflows with human review where appropriate
• Improving reliability, observability, and failure recovery in agent systems
  
• Exploring approaches to long-running and self-improving AI systems

What We're Looking For:

• We are looking for someone who understands modern AI systems and agent design, and is comfortable thinking about how multiple components work together.
• Designing agent architectures and workflows
  
• Working with multi-agent systems
  
• Designing feedback and evaluation loops
  
• Thinking about tool selection, planning, and task decomposition
  
• Building systems that can operate over multiple steps
  
• Evaluating where and why agents fail
  
• Reading current AI research and applying relevant ideas
  
• Building and testing ideas independently

Who Should Apply:

-We care more about what you have built and how you think about AI systems than your title or degree. Graduate students are ideal, but undergraduates and self-taught candidates with strong AI projects 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.