Consultant | Machine Learning Engineer | Public Sector

Who we are

ADC is a boutique Data and AI consultancy with offices in the Netherlands, Sweden, and Denmark, and an award-winning data design studio (CLEVER°FRANKE) embedded in the group.

We help data-driven leaders in complex, high-stakes environments move fast without losing control. We deliver four core outcomes: growing revenue and margin, moving from AI pilots to scale, reducing risk while staying confidently compliant, and building data products people love to use.

We are a collective of statisticians, designers, PhDs, and agentic AI engineers with deep expertise in the industries we serve: financial services, life sciences, healthcare, the public sector, retail, agriculture, and transportation. We do not arrive with generic tools and a slide deck. We walk in, work alongside the people who know the organisation best, and build solutions that actually run.

We call ourselves Way finders. Our clients trust us to navigate complexity and make it real: turning ambition into action in environments where the margin for error is small and the consequences of getting it wrong are real, for customers, employees, supply chains, and the bottom line.

We're leveraging our expertise in machine learning, cloud engineering, and MLOps to power ADC's growth and deliver unmatched value to our clients. Our Public & Society team is growing, and we are looking for a Machine Learning Engineer, who is curious, technically driven, and eager to grow with us. In this role, you will design, build, deploy, and maintain production-grade machine learning solutions while applying modern software engineering practices to real-world public sector challenges.

You will contribute to data and AI initiatives for public institutions, developing scalable systems that help improve public services, optimise operations, and enable data-driven decision-making.

You’ll be part of a cross-functional team, working alongside data engineers, data scientists, machine learning engineers, and public sector stakeholders to bring machine learning solutions from experimentation to production. You’ll help build scalable machine learning platforms, deploy robust ML solutions, and ensure they operate reliably, securely, and responsibly.

You will work in highly regulated environments where privacy, traceability, and reliability are critical requirements.

• Design, develop, deploy, and maintain machine learning systems that address complex challenges within public sector organisations.
• Build scalable, secure, and reliable solutions that support critical public services and operational processes.
• Translate business challenges into practical, production-ready machine learning applications that create measurable impact.

• Develop and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, model training, deployment, monitoring, and continuous improvement.
• Apply MLOps best practices using technologies such as Azure, Databricks, MLflow, Docker, Airflow, and CI/CD tooling.
• Ensure machine learning systems are scalable, resilient, observable, and maintainable in production.

• Build and implement machine learning solutions that meet high standards for security, privacy, transparency, and governance.
• Contribute to architectures that support regulated and mission-critical public sector environments.
• Implement model governance, monitoring, explainability, and compliance practices throughout the machine learning lifecycle.

• Work closely with engineers, architects, data scientists, and client teams to deliver end-to-end machine learning solutions.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
• Continuously improve engineering practices, architectures, and ways of working to deliver sustainable, high-quality outcomes.

At ADC, we're not just consultants. We're leading experts in Data & AI, using our expertise in strategy, business operations, and advanced analytics. What unites us is a shared way of working: breaking down complex challenges to change how organisations operate.

For this role, that means:

• A strong technical academic background:
  Computer Science, Machine Learning, Artificial Intelligence, Software Engineering, Data Engineering, or a similar technical field.
• Relevant professional experience: 3+ years of experience in Machine Learning Engineering, AI Engineering, Data Engineering with an ML focus, or a similar role, preferably within large and complex organisations.
• Hands-on experience across the machine learning lifecycle:
  Building, deploying, and maintaining production-grade machine learning solutions using Python and modern software engineering practices. Experience across the machine learning lifecycle, including data…