Computer Vision Engineer

What if you could help millions of people use a tool that has a real impact on their everyday life? That’s the opportunity with Envision’s small but passionate team. We empower people who are blind or have low vision to access everyday visual information for themselves. Because it isn’t just information. It’s knowledge, independence, and possibility.

The Product

Envision products articulate visual information into speech. The Envision App is free for everyone — It uses your smartphone’s camera to speak out written information, describes surroundings and objects, and even tells you who’s nearby. Excelling in all kinds of text and object recognition, Envision can read the text in over 60 languages. Be it handwritten notes, text on food packages, or the pages of an entire book.

Our Envision Glasses meanwhile brings our award-winning software to smart glasses, enabling the unprecedented experience of unobtrusive access to the visual world. With features ranging from real-time text recognition, to voice controls and even hands-free video calling, Envision Glasses open the door for the future of wearable assistive technology.

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The Role

Computer vision plays a central role in Envision. Our computer vision models help thousands of visually impaired people the world over to read documents with complex layouts, recognise faces of their friends and family and so much more.

As a Computer Vision Engineer, you will be responsible for pushing our existing models as close to the state of the art as possible. The role also involves constantly keeping an eye out for new opportunities that might arise as the field itself advances.

This role offers a lot of room for learning and growth in the areas of applied computer vision and mobile deep learning. The models you'll be working on will not just deployed on mobile devices but also wearables like the Envision Glasses which we believe will be the next wave of computing.

What are we looking for:

• BS/MS degree in Computer Science, Math, related technical field or equivalent practical experience
• Minimum of 2 years of Deep Learning and Computer Vision experience
• Familiarity with CV and DL fundamentals like feature extraction, CNN, supervised machine learning, transfer learning and distributed deep learning
• Strong grasp of OpenCV
• Familiarity with one of the following deep learning frameworks → TF/TF Lite, Pytorch or Keras
• Familiarity with GPUs & CUDA
• Familiarity with compression / optimisation of neural networks for mobile deployment is a huge plus.

What we offer

• Be part of a diverse, award-winning team: We are a team of 11 (and growing!) diverse dreamers, doers and thinkers based in The Hague, The Netherlands. Part of our team works remote, and we come together every Friday to catch-up over a drink or a game.
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• Have a global impact at scale: We are a young company, but we have a global impact. We have users in 200+ countries and we aim to be as inclusive as possible.‍
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• Sell a product people love that solves real problems: Our greatest source of inspiration and motivation are our users who love our product which truly enables them to be independent in their everyday lives. We are pioneering real-life applications of technologies like AI for good.
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• Gain new skills fast: Because we are a close-knit team of domain masters we are always learning from each other in order to work more synchronously. Your mind, abilities, and product sense will expand every day.‍
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• We take care of you: Competitive compensation package, while covering the cost for travel and relocation if needed.

Our Process

• 45-minute Screening call
• Round 1: Take home assignment
• Round 2: Dissecting the assignment, pair programming & code reading
• Call to discuss the offer
• Joining the team 🎉

How to Apply

Sound like a good fit for you? Please email us at careers@letsenvision.com and include:

• This role's title in your subject line, it'll help us to sort through the emails.
• Send your resume and any links that best showcase relevant projects you have built and done. For instance, your portfolio, LinkedIn, Github or writing samples.
• Keep it short and sweet.

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