Hi! My name is Gijs, and I joined Xomnia as the first Machine Learning Engineer as part of the Machine Learning Engineering Development Program. In this blog I’d like to tell you more about this program and my experiences with it so far.
What is Xomnia’s MLE Development Program?
The MLE Development Program is meant for data scientists, data engineers and machine learning engineers with at least one year of relevant working experience who are looking to further develop themselves in both the science and engineering aspects of the data profession.
Data science and data engineering are strongly interwoven in a lot of data projects, so companies are looking more and more for machine learning engineers that are able to solve data challenges from start to finish. By following this program, you can make up for the skills you think you currently still need to work on to become a full-fledged machine learning engineer. Before I go into more details about the program, let me first introduce myself...
A little bit about myself...
In 2018, I graduated with a degree in econometrics from the University of Amsterdam. Following graduation, it seemed like a logical next step to become a data scientist, so I immediately started working at a data science consulting company. Econometrics is a very theoretical study that focuses mostly on mathematics and statistics, so right after my graduation I didn’t even know what ‘data engineering’ was. But, as mentioned before, because data science and engineering very often go hand in hand, I naturally started to gain more engineering experience whilst familiarizing myself with many of the practical aspects of working on data science projects.
During this process, I found out that I enjoyed working on the engineering aspects of data projects a lot more than I did working on the science aspects. The reason for this is that, in my opinion, data engineering has clearer goals than data science and there is less insecurity. Instead of working to possibly increase a machine learning model’s performance or searching for possible relationships between different variables, data engineering is more like software development in that you are setting up infrastructure or deploying a model and you will usually know when you are finished. Being able to track my progress gave me a lot more satisfaction in my work. Because of this, I set my sights on becoming a data engineer after my first year of work.
I started taking on as many data engineering tasks as possible in my projects, and during my personal development time, I tried to learn a lot about cloud technologies. After another year of work, I had learnt quite a lot about engineering already. However, I knew that there were still many aspects of the data engineering field that I knew little about because, as other data professionals may recognize, I did not get to experience every aspect in the projects that I was working on. Not wanting to get behind in my development, I slowly started to look for a new job. Coincidentally, a few weeks later, I got approached by Xomnia and after a few more weeks I signed my new contract!
MLE Development Program’s structure and content
During the application process, applicants are able to express their wishes about what aspects of the data profession they would most like to develop themselves on and what kind of project they would like to work on.
Once a talent gets hired, Xomnia’s talent acquisition and account management teams will then start to carefully match the participant to an available project. Usually a project has a bit more focus on one of either data science or engineering. In my opinion, this makes for the perfect opportunity to get to know more about the field that you have the least experience with. In this way, you could enable yourself to develop and deploy machine learning models in the cloud and also extract and store all of the data that your model requires!
The MLE Development Program lasts either one or two years. After you have been matched with a project, you will spend every Monday to Thursday working for your client. For the first year of the program, you will get to follow a technical training every Friday morning. The training subjects have been carefully selected by Clement, the program’s technical supervisor and senior machine learning engineer, to make sure that all of the most relevant aspects of the data profession will be covered. Most of the training is provided by Xomnia’s core team members that already have lots of practical experience with their corresponding subjects.
One big advantage of the MLE Development Program is the very high quality of the training, because Xomnia has already provided data science and engineering traineeships for years. This allows the ML engineers to skip the steepest parts of the learning curve for different types of data skills, since in the data profession nothing will get you up and running as quickly as someone more experienced sharing code with you, explaining how everything works and sharing possible pitfalls to look out for.
Another important advantage is that by receiving all kinds of training for 52 consecutive weeks, you will learn about all of the most relevant data concepts and technologies, which will equip you with the knowledge of what technologies or concepts to apply whenever a new type of data challenge encounters you. This is especially advantageous because, as mentioned before, most data professionals won’t naturally gain experience in all aspects of their field, simply because the content of data projects is tailored for every employer/client. Because of these advantages, all of the training so far has been really valuable to me.
Why work for Xomnia?
Some of the applicants for the program so far have wondered why they should work for a client through Xomnia instead of just working for a company directly. The biggest reason why, in my opinion, is that next to being able to develop yourself through the training program, you also have the knowledge and experience of Xomnia’s core team at your disposal.
Xomnia's team consists of many medior and senior data professionals with all kinds of backgrounds. There is at least one expert on every data subject that you can think of and everyone loves to share knowledge and help others. At my client, I am the only person who knows anything about data engineering, but so far I have not felt overwhelmed by the difficulty of the work even once because I have been able to ask questions to the core team and have them verify my ideas at any time during the week.
In addition to this, the development program’s social supervisor, Lisanne, who is also an experienced data scientist and consultant, takes good care of the participants by regularly checking in with us to make sure we remain able to develop ourselves optimally. She’s also always available to help if any problems occur at the client and will support the program’s participants in setting goals for their personal development. Another thing I personally love about the program is that Fridays are very different from the rest of the working week, which makes Thursday evenings already feel like the weekend ;)
The culture at Xomnia
Last but not least, I need to tell you a bit about Xomnia’s culture, of course. I haven’t worked for Xomnia for very long yet, but I can already say that I’m proud to be a part of the Xomnia community. What really adds to the community feeling is that the management, commercial, marketing and talent consulting teams are truly involved with the data professionals and that a big emphasis is being put on sharing knowledge and creating transparency within the company. Everyone is very cheerful and helpful and the atmosphere is really open and accepting. We also have designated “CFOs” (Chief Fun Officers) that organize fun events/trips and extensive “vrijmibo’s” (Friday afternoon drinks), though at the moment our get-togethers are mostly digital, of course. All in all, I am really happy being employed by Xomnia and the MLE development program is an incredibly educational experience that I can wholeheartedly recommend to everyone who is still in the early stages of their career!
Interested in joining our Machine Learning Engineering Development Program? Click here to view our vacancy.