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Applied Research Scientist - Applied Research Lab at Element AI
Montreal, CA

What is the Applied Research Lab

Our Applied Research Lab is a place of innovation and ambiguity; a place where world-changing ideas are dreamed of and tested because we believe the Lab has the potential to transform the world of AI and change the lives of people around the world.

In the Lab we explore and refine our bold vision to build the future of AI. We execute research programs with high uncertainty to provide key research learnings that orient Element AI's product and component roadmap. This is where the ideas that differentiate us are born.

Your Job

As an applied research scientist working in the Lab at Element AI, you will work in a dynamic, diverse, cross-functional team and use your creativity to develop cutting edge machine learning solutions to difficult real-world challenges.

You will be given real datasets that aren’t perfect and wrangle problems that don’t often have a solution… and if your proposed solution fails, you may have to throw everything out and start afresh with a different hypothesis. But, this allows to continuously learn with your team and share both failures and learnings with the rest of the organization (fail parties are the best!).

You will work with your team to assess possibilities and provide potential solutions to vaguely defined problems. You will be expected to both do the necessary research to propose appropriate models/techniques and to have the necessary expertise to implement and train the models yourself. Where useful, you will not hesitate to employ classical machine learning methods, but you are keen on the idea of pushing the boundaries of deep learning and AI.

What do you need to be happy and successful in that role

You have significant understanding of the underlying theory of deep learning, operation research or related AI field. This expertise can come from extensive studies, previous industrial experience or awesome self-taught projects you have done on a personal basis.

You're also a solid programmer and you're comfortable doing scientific programming as well as software development and do not mind getting your hands dirty in various coding and engineering tasks. This includes embracing modern devops principles to development and working in a setting where code is expected to be shared and peer-reviewed.

You understand that running a model on the varied and often noisy data that arises in an imperfect context differs significantly from running it on a clean academic dataset, and that modifying a model or technique to work in that setting can be a significant and sometimes frustrating challenge. You embrace this challenge and may even have previous experience tackling it.

You learn autonomously and will enthusiastically stay up to date in the literature and techniques of your field while participating in the various learning opportunities we offer.

Above all, you fundamentally embrace the idea that research and innovation in an applied setting is a difficult, exciting and an incredible opportunity.