Machine Learning Research Intern
Joko

Joko

Machine Learning Research Intern

Spoločnosť

Joko

Joko

  • Mobilné aplikácie, Umelá inteligencia / Machine Learning, FinTech/InsurTech
  • Od 15 do 50 zamestnancov

Pracovná ponuka

Machine Learning Research Intern

Who are they?

At Joko, we leverage technology to help our users shop smarter: we help people preserve their purchasing power, buy more responsibly, and save time — all at once. Our ambition is to have a positive impact on the everyday life of hundreds of millions of consumers around the world. To achieve that, we have built an app as well as a smart browser that provide users with:

  • online and in-store cashback
  • automatically applied coupon codes
  • interest-free ‘buy now pay later’ on any shopping website
  • information on their purchases’ carbon emissions
  • and much more!

Joko was created in 2018 by Xavier, Alexandre, and Nicolas and the team has reached great milestones already:

  • 1.8m+ users
  • 1600+ merchant partners
  • €12m+ raised from leading European investors
  • 45 team members
  • €10b transactions processed to date

If you want to know more about Joko, check out this page.

Joko
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Job description

As a Machine Learning research intern at Joko, you will work on the automatic analysis of web pages, which is central for many core features of the smart web browser (and of the smart browser extensions) that we are currently building. For instance, your work will be key to delivering functionalities such as price tracking, product comparison, or universal one-click purchase on any e-commerce website, independently of specific website designs. Your work will also lay down the foundations of a radically new type of web browser, able to recognize and transform elements in real time on any website, in order to offer a unified and smooth shopping experience to our users.

You will typically work on the following problems:

  • Webpage classification: to detect if a webpage is a checkout page, a basket page, a product page for instance.
  • Webpage element classification: typically to identify web page elements such as prices, product images, user reviews, product descriptions, product features, credit card fields, shipping details forms, etc.
  • Automatization of user journeys: for instance, to automatically complete a checkout flow on behalf of the user.

Solving these problems requires digging deep into how webpages are transformed and rendered by web browsers, and find the right level of abstraction for the algorithms. In particular, you will work on the DOM structure (Document Object Model), which is a tree data structure that plays a central role in the functioning of web browsers. As the DOM is a tree, it can typically be leveraged through graph neural networks. But as it also contains very rich text and image data, these graph algorithms can be combined with NLP and Computer Vision algorithms to achieve maximum performance. You will also work on real-time inference and the embedding of your algorithms on devices with limited CPU and memory.

The literature on these subjects is still in its infancy, and exploration will represent an important part of the internship, through experiments, literature reviews, and theoretical developments. You will have full ownership of your projects, and the liberty to orient the research direction of your internship based on your results and what you consider promising amongst directions we determined.

You will work closely with the engineering team that will be here to help you integrate coding best practices into your research, and to give you an insider look into modern software development. You will also have the possibility to integrate some of the algorithms you designed into our product, and monitor their impacts on hundreds of thousands of users.

Your responsibilities:

  • Research: You will work on all steps of the research process – you will formalize the objectives of your work, conduct literature reviews to have a deep understanding of the problems, design new algorithms, analyze them both theoretically and experimentally, and collect and transform relevant data for your experiments.
  • Exploration & ownership: You will participate in orienting the internship towards research directions you deem valuable to our users.
  • Implementation, deployment & monitoring in production: Helped by the engineering team, you will be responsible for integrating into our product the most scalable and robust algorithms you will have worked on. Finally, you will monitor their impact on our users.
  • Processes: You will help improve our R&D tools, processes, and organization.

Preferred experience

  • Problem solver: You have strong analytical skills, you are creative, and you love solving complex problems.
  • Fast learner: You are comfortable in any technical environment and are able to quickly learn new technologies and new practices.
  • Programming skills: You have experience with writing code and are willing to improve on it. You have experience with Python and Python Machine Learning frameworks.
  • Attention to details: You know that the devil is in the details, and you have talent for spotting flaws when they exist.
  • Tech savvy: You are constantly looking at emerging technologies and you keep a close eye on the latest trends in the domain.
  • Efficiency: You are fond of productivity tools and able to deliver on time on projects with many stakeholders.
  • Mindset: You have an entrepreneurial mindset, you like challenges, you welcome feedback and you are willing to get better every day to reach excellence.
  • Communication: You have strong written and verbal communication skills, and you are able to explain something complex with simple words.
  • Languages: You are fluent in English both written and spoken, as we are expanding internationally soon. Mastering French is not required.
  • Education: You are a graduate student in a Machine Learning master.

Nice to have:

  • You have experience with research, from past internships or projects
  • You have knowledge in web automation and/or in web browser development
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