Research Scientist (Computer Vision & Applied AI) - Hybrid (Fulltime)

HireOn; Montreal; Hybrid; CAD 80,000 - 120,000; Full time

Job summary

An innovative firm is seeking a Research Scientist specializing in Computer Vision and Applied AI. In this hybrid role, you will lead groundbreaking research, focusing on developing advanced AI solutions to tackle complex challenges in vision models and deployment. Collaborate with engineering teams to transition research into production and publish your findings in top-tier journals. This position offers the chance to work on cutting-edge technology and contribute to the future of AI, making a significant impact in a rapidly evolving field. If you're passionate about pushing the boundaries of AI and computer vision, this is the opportunity for you.

Qualifications

• PhD or Master’s in Computer Science or related field required.
• 2-5 years of research experience in AI, robotics, or autonomous systems.

Responsibilities

• Conduct advanced research in AI and computer vision for real-world challenges.
• Design and optimize models for tasks like object detection and segmentation.

Skills

Machine Learning Fundamentals

Deep Learning

Computer Vision

Python

C++

PyTorch

TensorFlow

OpenCV

Robotics

3D Perception

Education

PhD in Computer Science

Master’s in Electrical Engineering

Tools

PyTorch

TensorFlow

OpenCV

Scikit-learn

Job description

Position: Research Scientist (Computer Vision & Applied AI) - Hybrid (Fulltime)

Location: Montreal, Quebec Office (Hybrid)

Type: Research & Technology (R&T)

About Us

For our client, we’re hiring a curious and innovative AI/Computer Vision Research Scientist to lead the discovery, development, and integration of advanced AI solutions in computer vision. You will work on cutting-edge problems such as robust vision models, frugal learning, and deployment of certifiable AI systems. The role involves creating PoCs, prototypes, and demonstrators to validate ideas and accelerate their adoption.

Key Responsibilities

• Conduct advanced research in AI and computer vision, focusing on areas like image and video processing, deep learning, and 3D perception to address complex real-world challenges.
• Design, implement, and optimize state-of-the-art models for computer vision tasks such as object detection, semantic segmentation, classification, tracking, and scene understanding using both conventional and deep learning approaches.
• Explore and develop frugal learning techniques, including few-shot and zero-shot learning, to build models that perform effectively with limited labeled data, ensuring scalability and generalization.
• Collaborate with engineering teams to build prototypes and transition research to production.
• Publish findings in top-tier journals/conferences; contribute to patents and innovation.
• Work with academic/industry partners (e.g., NSERC, MITACS).
• Translate business needs into research roadmaps and system requirements.
  
  

Required Skills & Experience (MUST HAVES)

• PhD or Master’s in Computer Science, Electrical Engineering, or related field.
• 2–5 years of research in AI, robotics, autonomous systems, or related domains.
• Strong in machine learning fundamentals, CNNs, Transformers, foundation models.
• Proficient in Python, C++, PyTorch, TensorFlow, Scikit-learn, and OpenCV.
• Experience with diverse sensing modalities: RGB, Infrared, LIDAR, RADAR, etc.
• Solid understanding of experimentation, optimization, and model evaluation.
• Publications in NeurIPS, CVPR, ICCV, ECCV, AAAI, or PAMI.
  
  

Skills: classification,few-shot learning,opencv,robotics,deep learning,object detection,machine learning,computer vision,tensorflow,c++,pytorch,scene understanding,video processing,python,3d perception,ai,tracking,image processing,semantic segmentation,research,scikit-learn,zero-shot learning