Applied AI Research Scientist
Industry Professionals
Date: 1 week ago
City: Montreal, Quebec
Contract type: Full time

Job Title: Applied AI Research Scientist
Location: Montreal, Canada (Hybrid)
Employment Type: Full-time
Experience Level: Mid-Senior Level
Industry: Artificial Intelligence / Computer Vision
Job Sourced By: Industry Professional sourcing candidates for its client based in Canada
About The Role
Our client, a leading innovator in AI and Computer Vision, is seeking an Applied AI Research Scientist to join their Montreal-based Research & Technology team. This hybrid role offers an exciting opportunity to contribute to cutting-edge innovation in a multidisciplinary environment. The ideal candidate is a highly motivated, creative thinker with strong technical expertise, passionate about developing novel AI methodologies and transforming them into scalable, real-world applications.
Requirements
Location: Montreal, Canada (Hybrid)
Employment Type: Full-time
Experience Level: Mid-Senior Level
Industry: Artificial Intelligence / Computer Vision
Job Sourced By: Industry Professional sourcing candidates for its client based in Canada
About The Role
Our client, a leading innovator in AI and Computer Vision, is seeking an Applied AI Research Scientist to join their Montreal-based Research & Technology team. This hybrid role offers an exciting opportunity to contribute to cutting-edge innovation in a multidisciplinary environment. The ideal candidate is a highly motivated, creative thinker with strong technical expertise, passionate about developing novel AI methodologies and transforming them into scalable, real-world applications.
Requirements
- Ph.D. or Masters degree in Computer Science, Electrical Engineering, or a related field with a focus on AI, machine/deep learning, or computer vision.
- 25 years of relevant research experience in robotics, autonomous systems, or related domains.
- Strong theoretical knowledge of supervised, unsupervised, self-supervised, few-shot, and zero-shot learning techniques.
- Hands-on experience developing and deploying computer vision models in academic or industrial settings.
- Solid understanding of image sensing modalities such as RGB, RADAR, Infrared, LIDAR, hyperspectral, thermal, etc.
- Expertise in deep learning architectures including CNNs, Transformers, and foundation models for tasks like detection, segmentation, and recognition.
- Proficient in Python and C++ with practical experience using ML/DL frameworks such as PyTorch, TensorFlow, Scikit-learn, and OpenCV.
- Demonstrated ability to design experiments, analyze data, and optimize models for performance.
- Strong written and verbal communication skills in English, with the ability to clearly convey complex technical concepts.
- Demonstrated ability to publish research in leading AI and computer vision conferences/journals (e.g., NeurIPS, CVPR, ICCV, ECCV, AAAI, PAMI).
- Excellent collaboration and teamwork abilities, including cross-functional communication with stakeholders.
- Proven experience with detection and segmentation algorithms for radar image data.
- Exposure to research collaboration with academic institutions (e.g., NSERC, MITACS) and industrial R&D partners.
- Familiarity with deploying trustworthy and certifiable AI models in critical applications.
- Background in developing AI models under resource constraints (e.g., frugal, few-shot, zero-shot learning).
- Patent contributions or innovation disclosures are a plus.
- Conduct advanced research in AI and computer vision, focusing on image/video processing, deep learning, and innovative algorithm development.
- Design and implement high-performing models for real-world tasks such as object detection, segmentation, and tracking.
- Lead exploration of frugal learning approaches to maximize performance from minimal training data.
- Validate robustness and reliability of machine learning models under practical deployment conditions.
- Transition research into functional prototypes and production-ready solutions in collaboration with engineering teams.
- Contribute to strategic research roadmaps by translating stakeholder requirements into innovative research objectives.
- Publish and present research findings at top-tier conferences and contribute to patents and internal knowledge bases.
- Serve as a subject matter expert in cross-disciplinary project teams, providing technical guidance and mentorship.
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