Applied AI Research Scientist

A Research and Technology (R&T) scientist specializing in frontier AI and computer vision is responsible for discovering, developing and integrating innovative methodologies to address complex challenges in these fields and to translate related concepts into Thales solutions. He/she proves their viability through the implementation of Proofs of Concept (PoCs) and guides their maturity growth through prototypes and demonstrators that will in turn illustrate and enable their full business potential.

To be successful in this role, curiosity for what is new, willingness to challenge the status quo, open-mindedness and out-of-the-box thinking are crucial. The individual should quickly learn and assess new techniques and technologies in order to decide whether to adopt, adapt or discard them. He/she also needs to be able to come up with new ideas, present them, challenge them and improve them continuously. The individual must possess deep, hands-on technical skills and be familiar with computer vision and AI for computer vision research methods and tools . The candidate must demonstrate a strong understanding of the scientific method and his/her ability to deliver quality content at all steps of the research process, from the capability to summarize the theoretical background of a novel domain to the dissemination of research outputs through peer-reviewed publications, patents or other means.

The scientist is part of a multi-disciplinary team. Strong team spirit and teamwork capabilities are mandatory. The ideal candidate therefore is able to demonstrate transverse skills that would facilitate the transfer of the work carried out to all stakeholders involved. She/he will contribute as a technical subject matter expert to Research and Technology projects across Thales and its business units. Therefore, good communication skills are required.

AI/Computer Vision Research Scientist Key Responsibilities:

• Conduct research in computer vision, focusing on vision-language foundation models (VLMs, Ve-LLMs, and vision foundation models), image/video processing, efficient and training-free learning algorithms, and edge-optimized CV models.
• Design, adapt, and evaluate foundation models, vision-language models, and multimodal perception models for real-world use cases.
• Develop methods for object detection, segmentation, visual reasoning, tracking, and scene understanding.
• Conduct pioneering research in frugal learning methods to adapt large-scale models using fine-tuning, few-shot learning, zero-shot learning, prompt tuning, LoRA, or other parameter-efficient techniques.
• Establish rigorous evaluation protocols for accuracy, robustness, uncertainty, bias, explainability, and generalization.
• Translate state-of-the-art research into prototypes, demonstrators, and deployable AI components.
• Collaborate with cross-functional engineering teams to translate research breakthroughs into deployable prototypes and production-ready systems.
• Work on problems of diverse scope to support the deployment of trustworthy and certifiable AI models in critical systems.
• Publish research findings in relevant/top-tier conferences and journals, in AI and computer vision, and contribute to publishing innovation patents.
• Demonstrate excellent communication skills with both technical and non-technical stakeholders.
• Demonstrate good judgment in selecting methods and techniques for obtaining better solutions.
• Develop excellent collaboration skills with academic or research organizations (e.g., NSERC, MITACS, etc.), and with industrial partners.
• Suggest, collect, and synthesize system requirements from stakeholders and contribute to shaping effective research and innovation roadmaps.

• Ph.D. or master’s degree in computer science, electrical engineering, or a related field with focus on computer vision, machine/deep learning and advanced AI models.
• Solid theoretical knowledge and understanding of machine learning fundamentals, supervised/unsupervised learning, self-supervised learning, efficient and few-shot learning.
• Demonstrate experience in developing and deploying computer vision algorithms in either academic or industrial settings.
• Strong understanding of various image sensing modalities, including RGB, RADAR, Infrared, LIDAR, hyperspectral, multispectral, RGB-D, thermal, ultrasonic, sonar, and structured light imaging.
• Strong knowledge of deep learning architectures for computer vision such as CNNs, Transformers, recent foundation models and related techniques used in object detection, segmentation and recognition.
• Solid experience in designing and executing experiments, refining models, optimization and data analysis.
• Proficiency in programming languages such as Python and C++, and in using ML frameworks such as PyTorch, Tensorflow, and Scikit-learn, and OpenCV library.
• A track record of research publications in relevant AI and computer vision conferences and journals, such as NeurIPs, ICCV, ECCV, CVPR, AAAI, and PAMI.
• Critical thinker with ability to communicating scientific work in a clear and effective manner.
• Excellent problem-solving skills with ability to think creatively and strategically.
• Excellent communication and teamwork skills.
• Strong written and verbal communication skills for effective collaboration and dissemination of research.
• Fluency in French and English (spoken and written).

• 2 to 5 years of research experience in robotics, autonomous systems, or similar fields.
• Practical knowledge of MLOps, software packaging, library/SDK development, engineering validation processes, and production-ready AI solutions.
• Proven expertise in developing and implementing detection and segmentation algorithms for radar images.

• Schedule: regular working schedule
• Physical Environment: mostly behind the desk environment (either in the office or remotely), occasionally on the field in an outdoor environment.
• Travel: occasionally, for field trials, attending conferences and/or meetings with colleagues in other regions of the world (e.g. Europe).

Thales provides an extensive benefits program for all full-time employees working 24 or more hours per week and their eligible dependents, including the following:

• Company paid Extended Health, Dental, HSA, Life, AD&D, Short-term Disability, travel insurance, Employee Assistance Plan and Well-Being program.
• Retirement Savings Plans (RRSP, DCPP, TFSA) with a company contribution and a match to a DCPP, with no vesting period.
• Company paid holidays, vacation days, and paid sick leave.
• Voluntary Life, AD&D, Critical Illness, Long-Term Disability.
• Employee Discounts on insurance (home, and auto).

Thales is an equal opportunity employer which values diversity and inclusivity in the workplace. Thales is committed to providing accommodations in all parts of the interview process. Applicants selected for an interview who require accommodation are asked to advise accordingly upon the invitation for an interview. We will work with you to meet your needs. All accommodation information provided will be treated as confidential and used only for the purpose of providing an accessible candidate experience.

This position requires direct or indirect access to hardware, software or technical information controlled under the Canadian Export Control List and/or the US Export Administration Regulations (EAR). All applicants must be eligible or able to obtain authorization for such access.