We are looking for an intern that will help us to research and create a new architecture to support Edge Machine Learning in our current platform.

For most current Machine Learning use cases models are deployed in a central (cloud) environment. This means that data has to be transferred to that central environment for further processing. With the growth of connected devices (IoT) and increasing amounts of sensor data that needs to be processed, it could be more secure and efficient to do the data processing (in this case machine learning) within the edge nodes themselves.

When this internship suits you  🤖

• You have a preference for a pragmatic, ambitious, small and close team.
• You are finishing your Software Engineering or related studies and are on the lookout for an internship.
• You want to have a great learning experience and want to apply your coding skills in a read world setting.
• You have demonstrable experience with JavaScript (preferably TypeScript based frameworks: Angular and NestJS). Experience with Python is a plus.
• Experience with deploying code with CI/CD pipelines and using Docker and Kubernetes.
• You are passionate about the world of Machine Learning and AI and believe it is of great importance to apply it in the fairest way possible.

What you will be doing  👩‍💻

In this internship we want to build the first version of our Machine Learning Edge deploy and management feature. This means that we should be able to manage edge machine learning deployments. Making sure to both have an architecture that fits into our current product and is:

• Efficient: in use of network resources and bandwidth,
• Accountable: no black-box predictions
• Secure: no concessions on security by moving away machine learning deployments to the edge.

You will be directly involved in our product team for the development of our Machine Learning serving platform. Our platform is mostly written in the TypeScript frameworks Angular and NestJS, so experience is important. The Machine Learning services are written in Python and Go, so experience there is an advantage too. Experience working with other parts of our stack Docker, Kubernetes and PostgreSQL will make this internship a good experience.

How to apply  🚀

Send your CV and cover letter to jobs@deeploy.ml.
Know someone who would be a great fit? Help us by sending them a link to this page.

How we proceed  🔎

All jobs and internships at Deeploy start with an assessment of your experience and motivation based on the CV and cover letter, progressing to 1-2 short interviews and a short mock project assignment.

Rather than trying to guess if we’ll work well together based on lengthy assessments or questionnaires, we instead invite promising candidates to work on a real life mock project with us. The mock projects is typically 4 hours of work, and give us an opportunity to get to know each other prior to pursuing an offer. It’s also a chance for candidates to make sure that it’s a good fit for them. For the case you will be invited to our office.

Hope to see you soon!