2026 Summer - AI/ML Intern

Description

Vacancy Status:

No: This posting is not for an existing vacancy within the organization and is open to new applications. (New Head Count)

AI Disclosure:

As part of the application process, Artificial Intelligence will be used in the hiring process for this role

Hybrid - This role is categorized as hybrid. This means the successful candidate is expected to report to Markham Elevation Center three times per week, at minimum.

Collaborating on innovation challenges, interacting with Industry leaders, attending cross-functional networking events and volunteering for community service activities.

About the Role:
As an AI/ML Research Intern on the AI Research team, you'll work on cutting-edge projects advancing vehicle autonomy, developing algorithms and models that shape the future of self-driving technology. This internship provides experience with real-world AI/ML systems, collaboration with leading researchers and engineers, and mentorship from experienced AV researchers to grow your skills in the autonomous vehicle industry.

What You'll Do:

• Lead research and prototyping of advanced machine learning methods, such as foundation models, vision-language architectures, diffusion models, image/video generation, self-supervised learning, imitation learning, and reinforcement learning.

• Prototype ML models that improve perception, prediction, or decision-making for autonomous driving.

• Collaborate with cross-functional teams, including perception, robotics, and systems engineering.

• Participate in technical discussions, share insights, and work towards publishing results.

• Currently pursuing or in the process of obtaining a Master's or Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field.

• Solid understanding of modern machine learning techniques, especially deep learning architectures (e.g., transformers, generative models, multimodal learning).

• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.

• Research experience in AI/ML, demonstrated through coursework, academic projects, or publications.

• Strong problem-solving skills and a collaborative mindset.

• Strong communication and presentation skills.

• Experience working and communicating cross functionally in a team environment.

• Able to work fulltime, 40 hours per week

• Familiarity with autonomous vehicles or advanced driver assistance systems (ADAS).

• Experience working with large-scale datasets and training ML models in high-performance computing environments.

• Intent to return to degree program after the completion of the internship/co-op

• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, CVPR, ICML, ICLR, AAAI, ECCV, RSS, ICRA, CoRL, or similar.

• Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches

• Experience building systems based on machine learning, reinforcement learning and/or deep learning methods.