MLOps Engineer

As an ML Operations Engineer, you work at the intersection of platform engineering and machine learning. You help contribute to an environment in which data scientists and ML engineers can easily and reliably develop, test, and deploy their solutions. By developing smart frameworks, templates, and packages, you make the work of your colleagues easier and faster.

Why working at Stedin gives you energy

• You help build solutions that have an impact on all ML applications within Stedin.

• You are given the space to think along about the further development of our ML platform.

• You work in a team where collaboration, knowledge sharing, experimentation, and continuous learning are central.

• You contribute to a reliable and future-proof energy supply for millions of customers.

• You get plenty of opportunities to further develop yourself, both technically and personally.

As an ML Operations Engineer, you play an important role in the further development of our machine learning platform. You ensure that colleagues can easily use reliable and user-friendly tools, frameworks, and processes.
For example, you develop Python packages that support the work of data scientists and ML engineers and accelerate the development of new use cases. Additionally, you manage and improve templates that simplify complex platform interactions for users.
In doing so, you look beyond one specific application. You think about solutions that are broadly applicable within different ML domains, from forecasting to image recognition. By developing scalable and reusable components, you help the entire team move forward.
Within this role, you work according to Continuous Delivery principles. In this, not only speed is central, but also quality, reliability, and a pleasant development experience for colleagues using the platform.

A day as an ML Operations Engineer

• The day begins with a joint team update in which ongoing activities are coordinated.

• Next, you work on developing and improving frameworks, packages, and tooling.

• Regularly, you participate in refinement and design sessions to further elaborate new ideas.

• Together with colleagues, you solve technical problems and explore innovative solutions.

• You also contribute to the growth of the team by sharing knowledge and experiences.

• Additionally, you work continuously on improvements that make the platform more stable, user-friendly, and better scalable.

All financial employment conditions at a glance:

• Good employment conditions are part of it. For instance, you receive a (maximum) salary of € 7,267.09 per month based on 40 hours per week.

• On top of your salary, you receive a personal budget of 24% (including 8% holiday allowance). You choose what to do with the budget: for example, extra salary or (up to max. 35.5) vacation days. In our calculation tool, you can see how it works

• Pension at ABP. Stedin pays 70% of the premium. And the choice to participate in our collective health and disability insurance.

On top of that, there is this:

• Modern home working facilities and a home working allowance of € 2.40 per day. At Stedin, we work 50% from home and 50% in the office.

• Travel to the office is done with the public transport-free scheme. That is a public transport card that you can also use in your free time. Or with the flexible travel scheme, where you choose, combine, and vary how you travel to work yourself and receive an extra allowance if you come by bicycle.

• A laptop and phone, or € 30,- net per month if you use your own phone.

• Plenty of development opportunities through training, events, and knowledge sessions.

You are critical, analytically strong, and think in solutions. You take ownership, work in a structured manner, and know how to bring others along with your ideas. Additionally, you are communicatively skilled and actively share knowledge within the team.

Furthermore, you have:

• At least 3 years of experience as a machine learning / software engineer or a comparable role.

• Strong programming skills in Python

• At least 1 year of experience with developing generic, reusable MLOps solutions.

• At least 1 year of experience with Azure, Databricks, Spark, DevOps strategies (CI/CD), and reliably managing or further developing production environments.

• A quality-oriented way of working, with attention to testing, monitoring, documentation, and manageability.

Want to make a real impact on the energy transition with your work? Apply directly via the button.