ModiFace Sr. AI Researcher

Research, innovation, and scale! Modi Face is the first tech company to be acquired by beauty giant L’Oréal and provides industry leading AR and AI technology to the most influential brands in the world. Modi Face’s patented technology is based on more than a decade of advanced facial recognition research at the University of Toronto and in collaboration with L'Oréal’s Research and Innovation team.

Our services include live 3D makeup and skin care simulation, anti- aging/skin-care diagnostics, and live hair colour simulation.

In this critical role, you will be part of our AI team that is supported by our MLOps team. You will work with bright and insightful minds, passionate professionals, and a welcoming community where your creative ideas are exceedingly valued.

NOTE:
This is a hybrid role; you are expected to be in the office a minimum of twice per week, at our downtown location.

• Conduct original, publishable research by advancing thestate-of-the-art computer vision (CV) and Generative AI(GenAI) models and algorithms
• Architect and develop CV and GenAI models and systems, focusing on efficient fine-tuning and on-device and in-cloud inference
• Mentor AI interns and collaborate closely with development teams to ensure successfultransferofresearchintorobust, production-ready solutions
• Strategically design, develop, and meticulously train advanced CV and GenAI models and algorithms, pushing the boundaries ofwhat'spossible
• Craft elegant, efficient, and maintainable code to build high-quality, scalable AI systems
• Proactively identify, evaluate, and integrate emerging AI technologies into the company's core technological capabilities, fostering a culture of continuous innovation
• Communicate complex research findings to diverse internal and external stakeholders and fostering collaboration
• Represent the company at leading AI conferences, publish research findings in top-tier journals andpatent novel AI advancements

• Master or Doctorate degree in computer science ora closely related field
• A comprehensive, end-to-end understanding of generative media applications and a passion for pushing the frontiers ofCV and GenAI.
• 5 - 7 years of work experience inAI research, demonstrating deep expertise in training, fine-tuning, and experimenting with CV and GenAI beyond mere black-boxutilization.
• Exceptionalproficiencyin Python, coupled with mastery of one or more leading deep learning frameworks (e.g.,PyTorch, Tensor Flow).
• Solid knowledge of programming languages and experience in the full lifecycle of ML systems, including development, debugging, and performance optimization
• Track recordof first-author publications atpremierAI conferencessuch as SIGGRAPH, ICML, ICLR,NeurIPS, CVPR, ICCV, or ECCV
• Ability to convey rigorous mathematical and scientific concepts to non-experts

At Modi Face, we believe compensation should be transparent, fair, and reflective of both experience and impact. The total compensation for this role is $150. Compensation is determined based on skills, experience, and the scope and complexity of the role. We value open conversations about compensation and are happy to discuss our approach at any stage of the hiring process.

When you join Modi Face, you’ll enjoy working with a team of passionate engineers and business professionals who are open and collaborative within an inclusive environment. We offer an opportunity to advance and refine your skills and talent.

• Along with a competitive salary, we offer access to Health & Dental Benefits, including company-sponsored wellness & training programs, Worldwide Profit Sharing, RRSP matching, employee assistance programs, exciting in-office and off-site social activities, team lunches, a stocked kitchen, and more!

At Modi Face, we create software used by diverse people globally. We value diversity and inclusion within our team to ensure we can deliver the fairest and accessible technology possible, so we welcome and encourage all persons to apply. Accommodations are available upon request for candidates taking part in all aspects of the selection process.