Data Science Intern

2 weeks ago

Montreal, Quebec, Canada Fujitsu Full time $60,000 - $90,000 per year

SUMMARY


We are seeking a highly motivated Computer Vision Intern to join our AI team and contribute to the development of state-of-the-art machine learning solutions. This role involves tackling challenging problems in computer vision, with focus areas including object detection and segmentation, multi-object tracking and association, self-supervised and metric learning, foundation models, and few-shot learning.

You will explore innovative approaches for visual recognition, enhance existing models, and optimize performance for real-time and edge deployment. This is a hands-on role requiring strong technical foundations, creativity, and a willingness to experiment with novel ideas in both research and applied settings.



RESPONSIBILITIES

  • Monitor, evaluate, and troubleshoot existing solutions, ensuring they operate as expected, and recommend improvements where necessary.
  • Prototype, benchmark, and improve computer vision models using deep learning techniques, including CNNs, transformers, self-supervised learning, metric learning, and foundation models.
  • Enhance and evaluate real-time object detection, segmentation, multi-object tracking, and object association algorithms.
  • Explore and implement few-shot learning strategies for scenarios with limited training data.
  • Optimize inference for edge devices (e.g., NVIDIA Jetson) using techniques such as quantization and pruning.
  • Collaborate with team members to integrate models into production systems.
  • Document findings, present results, and contribute to internal knowledge sharing.


QUALIFICATIONS

Required:

  • Bachelor's or Master's degree (completed or in progress) in Computer Science, Electrical Engineering, or a related field with focus on AI or computer vision.
  • Strong understanding of deep learning fundamentals, particularly CNNs, transformers, self-supervised and metric learning
  • Knowledge of object detection (e.g., YOLO, DETR), segmentation (e.g., UNet, SAM), and tracking algorithms (e.g., SORT, DeepSORT).
  • Experience with few-shot learning approaches.
  • Proficiency in Python and deep learning frameworks (e.g., PyTorch).
  • Working knowledge of Linux environment
  • Strong problem-solving skills and ability to work independently in a fast-paced setting.
  • Effective communication skills, both written and verbal.

Preferred (Assets):

  • Experience deploying models on edge devices (e.g., NVIDIA Jetson).
  • Prior academic or industry experience in computer vision R&D.
  • Exposure to cloud-based ML platforms (e.g., Azure ML)

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