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Intern Computer Vision Deep Learning Engineer Jobs in Toronto, ON

Autodesk

Intern, Machine Learning Developer

Toronto, ON · On-site +1

As an Artificial Intelligence / Machine Learning (AI/ML) Intern at Autodesk, you will contribute to ... Major in Computer Science, Engineering, Data Science, Statistics, or arelated field * Familiarity ...

Td

Machine Learning Engineer II

Toronto, ON

CA$154K - CA$199K/yr

Analytics, Insights, & Artificial Intelligence Pay Details: $154,000 - $199,500 CAD The pay details ... Our research broadly spans the field of machine learning with areas such as deep learning and ...

Magna

Machine Learning Engineer

Milton, ON · On-site

University Degree in Computer Science, or related field of study which includes Ai and Machine ... Execute ML / AI projects related to but not limited to the following Advanced Vision Systems ...

Clariti Cloud Inc.

Senior AI Researcher

Toronto, ON · On-site

... across computer vision, large language models (LLMs), multi-modal learning, and agentic AI ... Deep, demonstrated experience training and fine-tuning models from scratch using modern frameworks ...

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All JobsIntern Computer Vision Deep Learning Engineer JobsIntern Computer Vision Deep Learning Engineer Jobs in Toronto, ON

Intern Computer Vision Deep Learning Engineer information

What is the difference between Intern Computer Vision Deep Learning Engineer vs Intern Machine Learning Engineer?

AspectIntern Computer Vision Deep Learning EngineerIntern Machine Learning Engineer
Required SkillsComputer vision, deep learning, CNNs, Python, TensorFlow/PyTorchMachine learning, algorithms, Python, scikit-learn, TensorFlow/PyTorch
Work EnvironmentResearch labs, tech companies, startups focusing on image/video analysisTech companies, research labs, startups working on diverse ML applications
Industry UsagePrimarily in computer vision projects like object detection, image segmentationBroader ML projects including predictive modeling, NLP, recommendation systems

Intern Computer Vision Deep Learning Engineers focus on image and video analysis using deep learning techniques, while Intern Machine Learning Engineers work on a wider range of ML applications. Both roles require strong Python skills and familiarity with deep learning frameworks, but their project focus and industry applications differ.

What types of projects or tasks can I expect to work on as an Intern Computer Vision Deep Learning Engineer?

As an Intern Computer Vision Deep Learning Engineer, you can expect to contribute to projects involving image or video analysis, such as object detection, image classification, or facial recognition. Your daily tasks might include data preprocessing, annotating datasets, training and evaluating deep learning models, and assisting with model optimization for deployment. You’ll often work closely with senior engineers and researchers, gaining hands-on experience with real-world datasets and cutting-edge frameworks. Collaboration with cross-functional teams, such as software developers and product managers, is common to ensure your models address practical business needs.

What does an Intern Computer Vision Deep Learning Engineer do?

An Intern Computer Vision Deep Learning Engineer assists in developing and improving algorithms that enable computers to interpret and understand visual information from the world, such as images and videos. They often work on tasks like image classification, object detection, and facial recognition using deep learning frameworks like TensorFlow or PyTorch. Interns typically help with data collection, model training, evaluation, and sometimes deployment, all under the guidance of experienced team members. This role is a great opportunity to gain hands-on experience in machine learning and computer vision while contributing to real-world projects.

What are the key skills and qualifications needed to thrive as an Intern Computer Vision Deep Learning Engineer, and why are they important?

To thrive as an Intern Computer Vision Deep Learning Engineer, you need a solid understanding of machine learning fundamentals, computer vision concepts, and proficiency in programming languages like Python, often supported by coursework or personal projects. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and experience with image processing libraries like OpenCV are typically expected. Strong problem-solving abilities, curiosity, and effective teamwork skills help interns excel in fast-paced research and development environments. These skills are essential for contributing to innovative projects and adapting to the rapidly evolving field of computer vision.
What are popular job titles related to Intern Computer Vision Deep Learning Engineer jobs in Toronto, ON? For Intern Computer Vision Deep Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Intern Computer Vision Deep Learning Engineer jobs in Toronto, ON look for? The top searched job categories for Intern Computer Vision Deep Learning Engineer jobs in Toronto, ON are:
Intern Computer Vision Deep Learning Engineer jobs near you

Senior Computer Vision Engineer

Birdseye Solutions

Mississauga, ON • Hybrid

Full-time

Posted 14 days ago

Job description

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!


As a member of our team, you will have the opportunity to work on cutting-edge AI projects, collaborate with some of the brightest minds in the industry, and grow both personally and professionally. We believe in providing our employees with the resources and support they need to succeed, and we are committed to helping you reach your full potential.

In addition to a competitive salary and benefits package, we offer a range of perks and perks such as flexible work hours, remote work options, and opportunities for professional development. We also have a strong culture of teamwork and collaboration, and we believe that everyone's contributions are valuable and appreciated.


Responsibilities:

  • Design AI algorithms for a broad range of applications relating to the site-monitoring industry (facial recognition, OCR, object detection, object tracking)
  • Regular maintenance and improvement of existing services
  • Ensuring functionality and optimization of services via regular testing and feedback
  • Researching new technology and tools
  • Communicating in a clear and structured way with colleagues and managers to ensure optimal collaboration and teamwork
  • Following the agreed team or project processes and procedures, including reporting to superiors on status of project/release/task efforts and key issues


    Requirements:

    • Degree in any field relating to computational methods
    • Experience in designing classical and modern computer vision algorithms pertaining to any of the following: image denoising, facial recognition, OCR, object detection/tracking
    • Strong knowledge in modern AI methods with experience designing custom architectures
    • Excellent programming skills in Python or C++
    • Experience in MLOps is a plus
    • Experience with AI on Cloud/Edge is a plus
    • English speaking and writing proficiency


    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.

    #LI-Hybrid

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