What you'll be doing
The Advanced Analytics and AI team is the centre of AI excellence within CIBC and is leading the way in applying the best practices in artificial intelligence, predictive science, and machine learning, leveraging the latest technology and platforms. We collaborate with the leading academic institutes in the space of AI and machine learning to promote the exchange of ideas and enrich our talent. The Applied AI Research team is at the heart of making our vision for AI at CIBC a reality. Our work covers every aspect of the research life cycle, from partnering with Academia to building production systems. As an Applied AI Research Scientist, you will have an individual contributor (IC) role driving strategic direction through collaboration with AI Scientists, Engineers, and Product leaders across CIBC. You will play a crucial role in developing, improving, and exploring the capabilities of AI and Generative AI models.
At CIBC we enable the work environment most optimal for you to thrive in your role. To successfully perform the work, details on your work arrangement (proportion of on-site and remote work) will be discussed at the time of your interview.
How you will succeed
Applied AI competence: Tackle difficult and meaningful projects in domains such as foundation models, multi-agent AI, and responsible AI. Your work will make a significant difference in advancing cutting-edge technology and providing practical solutions to real-world problems.
Research skills: Evaluate and apply advanced research in deep learning, NLP, predictive modeling, and the related literature. Integrate state-of-the-art tools, technologies, and methods to support the development and implementation of large generative models.
Science-driven innovation: Work with other researchers, engineers, and product teams. Represent CIBC in the research community, collaborating with faculty members in the relevant AI research functions.
Who you are
You can demonstrate excellent coding skills and hands-on experience in large-scale model training with GPU acceleration. You haveadvanced interdisciplinary knowledge in deep learning, natural language processing, and big data. You have track record of impactful projects and publications at top-tier venues (NeurIPS, ICLR, Nature, etc.). You understand foundation model architecture, methods for pretraining and post-training, and model efficiency
You havea PhD in deep learning, or other related disciplines, and 3+ years in related research experience OR equivalent experience. Hands-on experience building end-to-end solutions with Large Language Models, or experience using cloud platforms and Databricks, are considered assets.
You are motivated by collective success. You value collaboration and embrace the power of an inclusive team that enjoys working together to achieve a shared vision.
Values matter to you. You bring your real self to work and you live our values- trust, teamwork and accountability.
#LI-TA
What CIBC Offers
At CIBC, your goals are a priority. We start with your strengths and ambitions as an employee and strive to create opportunities to tap into your potential. We aspire to give you a career, rather than just a paycheck.
We work to recognize you in meaningful, personalized ways including a competitive salary, incentive pay, banking benefits, a benefits program*, defined benefit pension plan*, an employee share purchase plan, a vacation offering, wellbeing support, and MomentMakers, our social, points-based recognition program.
Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients.
We cultivate a culture where you can express your ambition through initiatives like Purpose Day; a paid day off dedicated for you to use to invest in your growth and development.
*Subject to plan and program terms and conditions
Job Location
Toronto-81 Bay, 21st Floor
Employment Type
Regular
Weekly Hours
37.5
Skills
Artificial Intelligence (AI), Big Data, Critical Thinking, Deep Learning, Machine Learning (ML), Natural Language Processing (NLP), PL/SQL (Programming Language), Python (Programming Language), PyTorch, Statistical Analysis