Vector Institute

Role Description As a Vector Applied Machine Learning Intern, you will contribute to developing reusable software to apply and scale research breakthroughs in machine learning and AI. You will collaborate with some of the best and brightest AI developers and machine learning researchers and will work with leading industry sponsors and health stakeholders to apply AI. You will work closely with a technical lead on your software development projects for day-to-day direction. Start date: September 8, 2026 End date: December 18, 2026 Key Responsibilities - Work on AI software development projects following an agile methodology with teams that can include Vector AI software developers, professional staff, researchers, and industry sponsors; - Develop reference applications and model templates that apply AI research to real-world problems using public and private data sets, providing software for training, testing, operating, and updating models; - Develop open source software for applying AI research techniques to common problems; - Contribute to industry projects that apply AI research to shared problems, contributing engineering expertise, and assisting with operational issues; - Develop prototypes and proofs of concept; - Report and present on software development including status and results; - Other duties as assigned. Qualifications - You are a self-identified Black or Indigenous student or postdoctoral fellow (Indigenous ancestry or heritage – First Nations (status or non-status), Métis or Inuit) or a recent graduate. - You are in second year or higher, studying at a Canadian university or college, or a recent graduate within one semester of graduation. - Experience in machine learning and/or statistics. - Data engineering background working with messy real-world data is preferred. - Analytical skills to identify signals in data and feasibility of prediction. - Knowledge and experience of Python. - Experience with parameter and architecture tuning of deep learning algorithms is preferred. - Experience in leading open source deep learning software frameworks (e.g., PyTorch, Tensorflow, and CUDA). - Experience with or Interest in AI Systems development, large language models, recommender systems, or deep generative models is a plus. Nice to Have - Data science experience is considered an asset. - Software engineering background with experience in industry is considered an asset. - Experience working on systems level programming on SLURM is an asset. - You are creative and enjoy collaborating within a small entrepreneurial environment that is results-driven. - You are motivated by continuous learning and the opportunity to make a difference and a real contribution to the AI ecosystem. Compensation $25/hour. Position Status This posting is for an existing vacancy. Inclusion and Equal Opportunity Employment Vector believes AI powers possibility by advancing cutting-edge research and translating it into real-world impact through collaboration with research, industry, and government. Vector is committed to fostering a diverse and inclusive culture that reflects its values. The Vector Institute welcomes applications from all qualified candidates, including those who are Indigenous, 2SLGBTQIA+, racialized persons/visible minorities, women, and people with disabilities. If you require an accommodation at any stage of the recruitment or selection process, please contact hr@vectorinstitute.ai . The Vector Institute team will be happy to work with you to ensure your experience is as inclusive and accessible as possible. If you have any questions, please contact internships@vectorinstitute.ai . Please address applications (cover letter and resume) to Enoch To, Program Coordinator, Research Operations & Academic Partnerships, using the link provided. The deadline for submission is May 28, at 1:00PM ET. We thank all applicants for their interest in this exciting opportunity and will be in touch with those whose qualifications most closely match with our needs. Please note that all interviews are currently being held remotely.