Production ML Engineer: Turn Models into Reliable Systems

Trackunit

København

Hybrid

DKK 900,000 - 1,300,000

Full time

7 days ago
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Job summary

Trackunit is seeking an ML Engineer to turn models into reliable, maintained systems that construction companies use to make better decisions about 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.

We value strong Python skills, MLOps experience, and hands-on Databricks/MLflow expertise, with a focus on reliability and production-ready deployments.

Qualifications

  • Experience taking ML solutions into production and maintaining them beyond launch.
  • Strong Python skills and solid software engineering practices including testing, version control, reviews, and CI/CD.
  • Hands-on experience building ML workflows in Databricks and using MLflow for experiments.
  • Understanding the ML lifecycle from feature prep to retraining and deployment.
  • Ability to collaborate with data scientists to translate experimental code into maintainable systems.

Responsibilities

  • Turn models into reliable, maintained production systems used by customers.
  • Shape how ML is built, deployed, and improved across Trackunit.
  • Collaborate with data scientists, data engineers, and product teams to deliver production-grade solutions.
  • Balance reliability, performance, and cost while deploying machine learning solutions.

Skills

MLOps
Python
CI/CD
Cloud platforms
MLflow

Tools

Databricks

Job description

Trackunit is seeking an ML Engineer to turn models into reliable, maintained systems that construction companies use to make better decisions about 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.

We value strong Python skills, MLOps experience, and hands-on Databricks/MLflow expertise, with a focus on reliability and production-ready deployments.

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