Graduate or Starter ML Infrastructure Engineer Amsterdam.
One of our community members is a strong ML/AI customer data platform company. It is able to predict – real time – consumer behavior. Can you imagine what it takes to digest all data points from nearly one billion consumers and make strong predictions? Think about that again!
Fundament in infrastructure
In order to work with big data sets for prediction, a strong fundament in infrastructure has been setup for constant implementation, deployment and updating of current and new models, including release of new features. Does it sound exciting for you to become part of the machine learning infrastructure engineering team of this company?
Vacancy ML Infrastructure Engineer
Ideally we are looking for a just/nearly graduated student engineer in the beginning of his/her career. You finished you studies and have some experience in data engineering, cloud infrastructure engineering and/or full stack development. This experience is gained as a working student or you being a person who started coding and developing for fun since you became an adolescent or even from before in your wonder years.
Studied or not
The study you followed could have been Computer Science, Computational Science, Artificial Intelligence or likewise on a bachelor or master level. Are you an autodidact with a completely different study career, challenge us.
Might even that you are still studying and want to work more than study (meaning, finish your study while working).
What is required (the technical part)
- A good understanding of what machine learning is;
- Good understanding of Apache Spark;
- Good understanding of Kubernetes;
- Medium understanding of AWS (do you know only Microsoft Azure or Google Cloud Platform, do not worry, you might still fit);
- Medium understanding of Scala or Java.
Of course, there is much more, but if you have the understanding and (some) experience, we are sure the rest will follow!
What will you do:
- Building end-to-end tests for the ML applications;
- Managing local dev environment;
- Managing pipe lines;
- Maintaining applications (libraries, upgrades, versions etc…);
- System health monitoring;
- Kubernetes upgrades.
Become part of the team
The deploying, upgrading and testing may not sound challenging, but remember, new features and models will be developed and deployed. And as you are part of the team who makes it happen, you’ll be in the middle of it. So, your efforts and input are as much as important as the input of the principal ML engineer.
Depending on your personal skills and growth, new challenges will be offered.
Where would you like to go
By experience we know that good coaching and training is offered to make you grow. The company is big enough to make an engineering career, preferably in the fundament of machine learning and artificial intelligence applications.
For more information about this vacancy or if you want to explore if you fit, please contact Wouter at +31 (0)6 54 74 23 04. If you want to apply, please use the form below. An accompanying motivational message, is highly appreciated.
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