Machine Learning Engineer

Trackunit; Kolding; Remote; DKK 700,000 - 950,000; Full time

Job summary

Trackunit seeks an ML Engineer to turn models into reliable, maintained systems used in construction. You will operate at the intersection of data science and software engineering, shaping how ML is built, deployed, and improved across Trackunit.

You will leverage MLOps experience, strong Python skills, and Databricks/MLflow expertise to manage experiments, deploy models, and monitor performance in production, collaborating with data scientists to ensure robust ML lifecycles.

Qualifications

• MLOps experience taking machine learning solutions into production and maintaining them beyond release.
• Strong Python skills and solid software engineering practices, including testing, version control, code reviews, and CI/CD.
• Databricks expertise is a significant advantage.
• Hands-on experience building ML workflows in Databricks, tracking experiments and managing models with MLflow, and deploying and monitoring models in production.
• Understanding the ML lifecycle from feature prep to retraining and monitoring.
• Ability to work with data scientists to assess model performance and translate experimental code into maintainable systems.
• Experience with cloud platforms and tools for orchestrating ML workflows and serving predictions.
• Ability to communicate technical decisions clearly and connect engineering to customer needs.
• Experience training, tuning, and validating machine learning or deep learning models is a plus.
• Experience with time series, sensor, geospatial data, or distributed processing is a plus.

Responsibilities

• Turn models into reliable, maintained systems that production users can rely on.
• Collaborate with data scientists to evaluate model performance and address drift or data leakage.
• Shape ML pipelines and deployment strategies across cloud and on‑prem environments.

Skills

MLOps

Python

CI/CD

Testing

Code reviews

Technical communication

Tools

Databricks

MLflow

Cloud platforms

Experiment tracking

Job description

Most machine learning never makes it to production. Your job is to make sure ours does. We are looking for an ML Engineer who turns models into reliable, maintained systems that construction companies actually use to make better decisions about their equipment and operations. You will work at the intersection of data science and software engineering, shaping how machine learning gets built, deployed, and improved at Trackunit.

What’s in it for you?

• Bring machine learning into everyday use.
• Shape how we build and run ML.
• Work on interesting data challenges.
• Build alongside people with different strengths.
• Develop your craft and your career.

Who are you ideally?

• You have MLOps experience taking machine learning solutions into production and maintaining them beyond their initial release.
• You bring strong Python skills and solid software engineering practices, including testing, version control, code reviews, and CI/CD.
• Databricks expertise is a significant advantage.
• You ideally bring strong hands-on experience building ML workflows in Databricks, tracking experiments and managing models with MLflow, and deploying and monitoring models in production.
• You understand the ML lifecycle, from feature preparation and reproducible training to evaluation, deployment, monitoring, and retraining.
• You can work with data scientists to assess model performance, recognise issues such as data leakage and drift, and translate experimental code into maintainable systems.
• You have experience with cloud platforms and tools for orchestrating ML workflows and serving predictions. You can make sensible trade-offs between reliability, performance, and cost.
• You enjoy shaping solutions with others, explaining technical choices clearly, and connecting engineering decisions to customer needs.
• Experience training, tuning, and validating machine learning or deep learning models would be a plus.
• Experience with time series, sensor or geospatial data, or distributed processing would be a plus.

Our hiring process

Don't waste your time on writing the best possible cover letter for the job. We want you to create an impact that matters, and that's not in the cover letter.

• Virtual meet and greet. Meet with the Talent Acquisition Partner.
• A deeper conversation: We'll go into your experience and how you work, and you'll get a clearer picture of the team, the challenges, and what the role actually looks like day to day.
• Assignment-specific interview. We want you to get an insight into some of the concrete work tasks or projects related to the role. You will be given a case to prepare prior to the interview, and at the interview, you will present the case to relevant colleagues from across Trackunit, who you'll also work closely with in the job.
• If needed, throughout the process we will obtain references from former employers and do background checks for level specific, if you have not provided these yourself.
• Offer presentation and walk-through. We're lucky to have you!

Coming Together To Connect Construction

We're committed to construction - one of the largest industries in the world. Over the past two decades, Trackunit has been pioneering technological progress within construction. Today, we are not only a leading IoT provider but a thought leader, supporting and shaping the agenda for an entire industry on a global scale.

We believe in taking a people approach in everything we do. Being human-centric is not restricted to our products - it's a way of life at Trackunit. We're proud to be a truly global team. Our colleagues get together in hubs spread across the globe, but we embrace the idea of working remotely and in environments that inspire you. Everything we do, we do it to eliminate downtime and build the most useful industry for the world.

The question is: Are you in?