Join me for a week in the life of a Machine Learning Engineer at Enjins!
Here, we’ll provide you with the day-to-day tasks of a Machine Learning Engineer in our Utrecht Hub. Read through our agenda to get an overview of the diverse tasks ranging from project kick-offs to coding.

Morning: We start the day with a stand-up meeting, discussing the progress from last week and the upcoming tasks for this week. As a follow-up, we delve into designing a new data warehousing architecture with a snowflake schema for a Fintech client.

Lunch: On Mondays, the office is bustling with colleagues in Utrecht, providing the perfect opportunity to catch up on the weekend’s activities.

Afternoon: We tackle the debugging of a scraper for the Fintech company, fixing the Datetime format issue, and updating the SQL database with new Supplier IDs.

Morning: Our focus is on preparing a kick-off meeting for a new project with a Cleantech company. We discuss the project scope and expectations, convening in an online setting to accommodate colleagues from Berlin and Utrecht.

Afternoon: We work towards enhancing data models for better reliability, scalability, and security for the Fintech client. Moreover, we aligned on the planning for tomorrow’s visit to their office.

Morning: We’re at the client’s office, working on a forecasting model to predict prices using lagged time series correlation.

Afternoon: Implementing CI/CD in Gitlab is on the agenda to ensure smooth code deployment and minimize errors. As the day winds down, we participate in a “floor day” where we gain insights into the core business by spending time at the customer service desk and interacting with employees.

Morning: Today, we visited the office of a retail client to explore opportunities for continuing our partnership. We catch up on the current status and discuss potential directions.

Afternoon: The kick-off meeting at the Cleantech company takes center stage, where we ensure all necessary resources are in place for the project’s commencement. Afterward, we evaluate the meeting’s outcomes and prioritize tasks for the follow-up sessions.

Morning: We prepare for “Learn At Lunch” at the Enjins office, an event where colleagues share knowledge on diverse topics. Today, one of our colleagues explains how they used a vector database to implement customized LLMs (Large Language Models) for a client.

Afternoon: As we wrap up our workweek by finishing a long-waited PR, we head to Neude for drinks and bites with colleagues, including our new Machine Learning Engineer team members.

Being a Machine Learning Engineer at Enjins is diverse, involving algorithm training, project preparation, understanding business needs, and implementing engineering elements. The combination of technical skills and business understanding makes this job highly appealing. If you have any questions about the job, feel free to contact us through LinkedIn or the contact button below. We’re more than happy to help!