Aspiring Machine Learning Engineer

🤖 The Job

As a Machine Learning Engineer you will excel in building digital data-driven solutions for our clients. You will become an architectural genius that effortlessly designs, develops and deploys machine learning models.

We are a scale-up from Leuven (with co-working locations in Brussels and Ghent) that researches, designs and codes robust AI-solutions & platforms for various sectors. Our dedicated in-house team of data-specialists uses a pragmatic best-tool-for-the-job approach to optimise our clients' processes and decision making. With a strong focus on DataOps and MLOps we firmly believe in robust and production-ready solutions being an essential part to our work. The result? Our team provides clients a reliable foundation to make data-driven decisions.

More information about our Rootsacademy? 👉 https://dataroots.io/careers/rootsacademy

🎉 What you can expect at dataroots?

Ready to roll into your next adventure? Let’s meet! At Dataroots, we have prepared a 2-month training program for young graduates that gives you a strong foundation to start your career as a Machine Learning Engineer (Start date: September 2022). During these months you will be introduced to the world of AI, cloud, data, infraops and robust software design. After this period, you will start your first machine learning or data engineering project. You will continue to develop towards becoming an expert in machine learning and data science.

Our offices are the ideal workplace for people with a knack for innovation. Our languages? Python, Scala and Go. What we speak when we're not coding? English, because, with colleagues from Mexico or France, you'll enter an inspiring and internationally focused team.

Job requirements

💪 The Skills

• You are strongly motivated to become an excellent Machine Learning Engineer.
• You have a solid foundation in Machine Learning theory and have trained and/or deployed your first AI models.
• You're at ease with programming in Python, knowledge of Scala is a plus.
• You have been in contact with cloud platforms like AWS, GCP or Azure.
• You have heard of tools like Apache Spark, Beam and/or Kafka.
• You know that Kubernetes, Terraform and CI/CD aren't Star Wars characters. You are interested in learning about data-architecture and data-infrastructure.
• You have a knack for picking up on new technologies and frameworks.
• You have an analytics and solution oriented mindset.
• You have strong communication skills and look forward to helping clients in overcoming their challenges.
• You ideally have knowledge of English and Dutch, knowledge of French is a plus.

This list was probably a bit much. Don't worry, we don't expect you to tick every box from the beginning. Most of all: we are looking for colleagues with the same passion for personal and team development as the rest of us.

💰 The Offer

• An attractive salary package.
• Guidance by our experienced Machine Learning Engineers, Data Engineers and other experts.
• A training trajectory & budget focused on advancing your professional career.
• Training and seminars with your team and external experts to further sharpen your technical skill set.
• We let off steam during our fries & beers and monthly day@dataroots events #workhardplayhard.
• Your own innovation budget to work on cool, educational, challenging and/or opensource projects with others within your guild.

🇧🇪 Our main office is located in Leuven, with co-working spaces in Brussels and Ghent. These locations are always available for brainstorm sessions or team events. As a dataroots consultant, you will occasionally be doing on-site visits at our clients. However, most of our work is done remotely. At dataroots, we are actively adapting to this new way of working. ✌️

Ready for a new chapter as a Machine Learning Engineer at Dataroots? Great! Apply now! 🎉

How do you apply? Either choose the easy way and use the apply button or impress us with your skills by POSTing your resume via our /recruitment endpoint (you can find the docs here https://api.dataroots.io/v1/docs).