Lab Summary:
Samsung AI Research Center (SAIC) located in Toronto, Ontario, is currently recruiting outstanding scientists who have a passion for innovation in a collaborative environment with a focus on highly visible, challenging, and interdisciplinary projects. SAIC-Toronto is a recently established AI Center, and a key part of Samsung’s global AI Research efforts, with centers around the world (including Cambridge, Moscow, Mountain View, and Korea). Samsung’s global AI Research efforts seek to conduct long-term research with potential for direct impact on future Samsung products reaching hundreds of millions of users worldwide. SAIC Toronto is in the heart of Toronto, next to the University of Toronto, and at the epicenter of a vibrant AI community. Come join us!
Position Summary:
SAIC-Toronto is looking for strong candidates with expertise in computer vision, machine learning, and natural language processing.
Position Responsibilities:
We are looking for strong candidates with a solid theoretical and practical background in the following areas::
- Camera-based imaging and image manipulation, such as image denoising, image enhancement, super resolution, image/video editing, image-based rendering and scene manipulation.
- High-level computer vision, such as object detection and segmentation, video summarization, and representation learning.
- Multi-modal tasks, such as visual question answering and visual dialog, visual captioning, vision-and-language representation learning, and dialogue-driven image/video search, editing, and/or summarization.
- Generative models (large language models, diffusion models, and vision-and-language foundational models), including prompt design, fine-tuning and evaluation.
Required Skills:
- PhD in Computer Science or equivalent combination of education, training, and experience.
- Track record of publishing scientific papers in top conferences and journals
- Strong communication skills (written and verbal), motivation for international collaboration
- Self-motivated, independent, and able to work well in a fast-paced, collaborative environment
- Expertise in the latest applications of deep learning algorithms to problems in computer vision and natural language processing
- Theoretical knowledge of, and practical experience with, large language models, multimodal foundational models, and generative AI in general
- Solid technical and programming skills (Python/Java/C++, PyTorch/TensorFlow)
Special Attributes:
The ideal candidate will have experience in one or more of the above areas, while using advanced machine learning techniques, such as transformers and generative AI.
The candidate will have the opportunity to work with other top researchers and engineers, and to publish at top-tier conferences and journals. There is also opportunity to work with product teams developing applications for Samsung devices. This position is a great fit for researchers who want to be at the cutting edge of research, and at the same time have direct real-world impact.
Additional Information
Essential Job Functions
This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, and frequently operate standard office equipment, such as telephones and computers.
Samsung Research America is committed to complying with all Federal, State and local laws related to the employment of qualified individuals with disabilities. If you are an individual with a disability and would like to request a reasonable accommodation as part of the employment selection process, please contact the recruiter or email sratalent@samsung.com.
Affirmative Action / Equal Opportunity
Samsung Research America is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, or status as a protected veteran.
For more information regarding protection from discrimination under Federal law for applicants and employees, please refer to the links below.
