Werkstudent Machine Learning Infrastructure Engineer / Working Student - Amsterdam.
You have a high interest in (cloud) infrastructure engineering for ML & AI solutions (and less in the modeling / mathematical part). You seek a serious engineering side job where you learn and will be challenged. You would even like to write your thesis in this job.
Predicts answers on questions not yet to be asked
Analyticals IO connects clients to working students with a quantitative study to help each other grow.
One of our clients is a Machine Learning & Artificial Intelligence company that predicts (consumer) behavior based on large data sets that are processed real-time.
Their engine/solution is of such a high level, that it can predict the answer to be given on a question the consumer has not yet realized he/she is going to ask! That is some serious prediction we might say. And with this in mind, content can even be dynamically generated (experimental) to give the answer beforehand, so the consumer has no need to ask the question to the consumer department. Think about that! About the technology, about the solution, about your side job within this company.
From idea to model in production
Above mentioned should give you an idea about the technology and solutions used by our client. Their technological solutions are used by big corporate clients with millions of consumers as their customer. Last year, working students of Analyticals IO have been put in contact with this client to help out in data modeling. One of them came up with an idea – using his fresh brains – to develop a solution for smaller companies who are in need for a specific ML/AI solution that ‘predicts’, but without the need of data engineers and scientists on their, the smaller companies, side.
This idea was picked up with much enthusiasm by the company and the idea became a project version 0.1, 0.2 and so on. Mind you, the idea was fully worked out by the working student with guidance of senior engineers and modelers.
Challenge the status quo
Why this extensive description so far?
- The company does see the real value of young, fresh brains and has experienced it!
- The company offers guidance, challenge and wants to be challenged, hopefully by you;
- Working students with side jobs (werkstudenten met bijbaan) challenge the status quo.
The aforementioned project has reached the next step 1.0. And that is where your skills are needed: help bringing the solution in production and implement new features and models.
So, are you up to putting your skills and brains to work by becoming a werkstudent / working student ML Infrastructure Engineer?
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, you are not somewhere at the end of the food chain.
Depending on your personal skills, new challenges will be offered (or you will bring in new ideas which you may implement). How cool!
We think you are now a student and studying for example:
- Computer Science;
- Computational Science;
- Artificial Intelligence;
- Classical and quantum information; or,
Might be bachelor or master. You have a clear view of your future. Writing your thesis within this project is possible. Might make it even more challenging for you and it may become the substantiation of your work.
If you have a fellow student with whom you do all your projects, the company is ‘open’ for a you and a co-working student.
How to continue
Much more can be written (32 hours a week is unfortunately a must), but better to discuss in person. Feel free to call Wouter at +31 (0)6 54 74 23 04 to learn more or use the form below. An accompanying motivational letter, is highly appreciated.