Startup Careers

Be a part of our family by contributing to our portfolio companies’ innovation and success. Browse open positions below with Intel Capital portfolio companies.

Applied Research Scientist at Element AI
Tokyo, JP
We are putting together a world-class research and development team to build a platform enabling next generation AI-First businesses. As a research engineer in machine learning you will enjoy a unique opportunity to use your creativity both to pursue fundamental research and to apply cutting-edge techniques within applied projects. You will face diversified challenges and you may end up working on time-series, images, videos, control problems, etc. While doing so you will have access to the best hardware and you will be assisted by a team of IT experts and software developers, to ensure most of your time is spent on core R&D challenges.

Our research agenda covers many subjects and, based on your interests and our needs, you could explore generative models, reinforcement learning, constraint programming, etc. You will collaborate closely both with software developers and with scientists. In particular, you'll get the opportunity to discuss weekly with world-class academics from our Faculty Fellowship program, such as Aaron Courville, Joelle Pineau, Christopher Pal and Doina Precup. These collaborations will often lead to publications in the most important journals and conferences.

You have experience in machine learning, either through graduate studies or industrial R&D projects. You're also a solid programmer and you're comfortable doing scientific programming as well as product development. You can understand and implement techniques exposed in academic papers in your field.

You want to join us because you are passionate about:

Fundamental research in machine learning;
Explaining the data audit and data quality control to partners and clients;
Exploring the wide variety of contexts and situations in which ML can be applied;
Working with huge datasets and finding unexpected signal in them;
Using and discovering the best tools to build working prototypes of AI services;
Coding high-quality production code and continuously learning the best practices to turn research into delightful products;
Building strong collaborative relationship with scientists, software developers, and program directors;
Staying up-to-date on the scientific literature in your field, and even contributing to it by publishing in famous journals and conferences.
We want you to join us because you have:

A getting-things-done mindset with a desire not only to push the boundary of fundamental knowledge, but to turn it into products people love;
A Ph.D or M.Sc. in machine learning or a quantitative field and at least 3 years of industrial R&D experience;
The seniority of the candidate will be established through the interview process;​
A more experienced candidate could evolve into a leadership position as we grow the team;
Experience and mastery of scientific programming and libraries relevant to your field for example: Theano, TensorFlow​, NumPy, R, etc.;
Experience with at least one of the following programming language, preferably for the development of production code: Python, C++, Scala, Go, C#, F# , JavaScript, Java, etc.;
An open mind and a desire to learn the best language/technology to solve a given problem;
Experience working in a diversified team;
A history of shipping high quality code using cutting-edge techniques.
What we offer for your valuable work:

Highly dynamic, innovative, passionate, intrapreneurial team;
Open and inclusive company culture;
Worldwide competitive salary;
Participation in the company success through the Employee Stock Option Plan;
Participation in company employee benefits program;
Flexible hours (outside of core hours);
Autonomous, self-managed Agile teams.
We strongly believe in collocated team dynamic. We would be happy to work with you if you can join the team in our Montreal office.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.