Machine Learning Engineer (Intern)

London, England, United Kingdom · Research expand job description ↓

Description

We’re building the new identity standard for the internet.

Whether you want to open a bank account or hire a car, our lives are moving online. That means millions of everyday interactions now happen digitally—without ever meeting anyone face-to-face. Increasingly, our identities are becoming the new currency which we use to access online services. But with half the world being unbanked, and identity fraud on the rise, that’s becoming more and more difficult. So our mission is to create an open world, where identity is the key to access.

We use machine learning to assess whether a user’s government-issued ID is genuine or fraudulent, and then compare it against their facial biometrics. As a global leader in computer vision, our AI learns to identity fraud as it evolves over time. Our goal is to apply cutting-edge research to build powerful, simple products that drive inclusion and safety online—without compromising on user privacy.

That’s how we give companies like Revolut, Zipcar and Bitstamp the assurance they need to onboard users remotely and securely across 195 countries… and we’re just getting started!

Founded in 2012, we're a diverse, global team of 250 technologists spread across 6 countries. We've also received over $60m in funding from world-class technology investors including Salesforce and Microsoft.

You can learn more about our team and the work we do on our Onfido blog.

We use a lot of exciting technology. Our engineers are flexible about technology and pick the right tool for the job:

  • Python, Ruby and Elixir for our service code
  • React and Redux for frontend work
  • Tensorflow for Machine Learning / Computer Vision
  • Kubernetes and Docker to package and run services
  • AWS for underlying infrastructure

You can learn more about our product engineering team and the work we do on our Tech blog.

THE ROLE:

We’re looking for software engineers with expertise in machine learning and computer vision to help us shape and develop our ID verification solutions. We apply cutting-edge ML techniques in our core product to classify documents, identify physical forgeries and extract data.

What you will be doing:

  • Work closely with a group of researchers developing highly scalable machine learning/computer vision models.
  • Collaborate on projects that help shape the future of Onfido.
  • Participate in technical group discussions and research paper reading groups.

What you will accomplish:

You will contribute towards a publication in a relevant top conference, a feature that goes into one of our products or tools that improve the way we work. We will provide support throughout the project to help you accomplish these goals.

As a Machine Learning Intern, you will be able to work in one of the following areas:

  • Text detection and recognition
  • Barcode/QR code detection and decoding
  • Image quality analysis, noise removal and deblurring
  • (Deep) Generative models
  • Face analysis (detection, recognition, reconstruction, etc.)
  • Eye-tracking
  • 3D/Depth reconstruction
  • Physical material properties (BRDF) capture

Requirements

  • Enrolled in a Masters or PhD programme focusing on machine learning or computer vision.
  • Ability to write good code.
  • Knowledge of at least two of the following areas:
    • OCR
    • Computer Vision
    • Image Processing
    • Machine Learning
    • Deep Learning

Benefits

We're committed to making Onfido a fantastic place to work, so we go to great lengths to give you what you need to succeed. As an intern, you will benefit from:

  • A kitchen stocked with breakfast foods, snacks, drinks and fresh fruit
  • Subsidised gym membership, free yoga classes, company 5-a-side football and a weekly running club
  • Invited to company social activities (monthly dinners, Friday afternoon drinks and other events)

SALARY INFORMATION:

- £30,000 salary pro rata'd

We are an equal opportunity employer and value diversity at Onfido. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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