Public Sector ML Engineer: Build Scalable, Responsible AI

Amsterdam Data Collective; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Bonus structure

Co-ownership opportunities

Annual team events

Job summary

Amsterdam Data Collective seeks a Machine Learning Engineer to design, build, deploy, and maintain production-grade ML solutions for public sector challenges. You will work with data engineers, data scientists, and public sector stakeholders to bring ML from experimentation to production in regulated environments.

You will apply modern software engineering practices, ensure security and governance, and contribute to scalable, reliable ML platforms acrossAzure, Databricks, and related

Qualifications

• Strong technical academic background in CS/ML/AI/SE/Data Eng.
• 3+ years in ML engineering/Data engineering with ML focus.
• Hands-on across ML lifecycle: data prep, feature engineering, model development, deployment, monitoring.
• Familiarity with cloud platforms and MLOps practices.

Responsibilities

• Design, build, deploy, and maintain production-grade ML solutions for public sector challenges.
• Develop scalable ML platforms with reliable, secure operations.
• Collaborate with engineers, data scientists, and stakeholders to move from experimentation to production.
• Implement governance, monitoring, explainability, and compliance throughout the ML lifecycle.

Skills

Python

ML lifecycle

Communicate clearly

Fluent English

Fluent Dutch

Collaborative

Education

Computer Science

Machine Learning

Artificial Intelligence

Software Engineering

Data Engineering

Tools

MLflow

Databricks

Azure ML

Docker

Airflow

Job description

Amsterdam Data Collective seeks a Machine Learning Engineer to design, build, deploy, and maintain production-grade ML solutions for public sector challenges. You will work with data engineers, data scientists, and public sector stakeholders to bring ML from experimentation to production in regulated environments.

You will apply modern software engineering practices, ensure security and governance, and contribute to scalable, reliable ML platforms acrossAzure, Databricks, and related