AI / Machine Learning Engineer

• Location: Eindhoven
• Salary: € 5.500 - € 6.500
• Living in NL already
• No ZZP allowed

Introduction

Are you passionate about applying machine learning to drive innovation and create tangible value? Do you see how advanced ML can transform the semiconductor industry? Would you like to join a team building cutting-edge ML solutions for a global data analytics platform? If so, we want to hear from you.

Job Mission

As a Machine Learning Engineer in the Data Analytics organization, you will design, develop, and deploy ML models and algorithms that support teams across the company. You will collaborate with data scientists, engineers, developers, and business stakeholders to deliver ML-driven products and services. You will also help shape and maintain the AI services within the enterprise data analytics platform in the IT Chief Data Office.

Roles and Responsibilities

• Design, build, and deploy scalable, maintainable, and traceable machine learning models.
• Collaborate with cross-functional teams to translate business needs into ML-driven solutions.
• Handle data preprocessing, feature engineering, model development, evaluation, and monitoring.
• Integrate ML models into production environments (cloud and/or on-premise).
• Stay current with the latest ML technologies and apply them as appropriate.
• Participate in code reviews, testing, and documentation to ensure quality.
• Monitor and maintain deployed ML models to meet performance, reliability, and accuracy targets.
• Contribute to best practices and standards for machine learning across the organization, including CI/CD templates, MLOps frameworks, and process guidelines.
• Develop and apply containerization strategies for ML applications (e.g., Docker, Kubernetes).

Education and Experience

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
• 5+ years of relevant experience in machine learning, data science, or similar roles.
• Strong experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.).
• Proficiency in Python.
• Hands-on experience with Microsoft Azure; knowledge of GCP is a plus.
• Solid understanding of MLOps practices, data preparation, feature engineering, model evaluation, and CI/CD.
• Proven track record deploying and maintaining ML models in production.
• Awareness of standards and regulations such as GDPR, ISO 27000 is a plus.
• Experience mentoring junior team members and improving AI service capabilities.

Skills

• Strong passion for machine learning and solving real-world challenges.
• Customer- and value-driven mindset in developing ML solutions.
• In-depth knowledge of ML algorithms, techniques, and best practices.
• Understanding of data architecture and data modeling.
• Familiarity with agile and scrum practices.
• Strong background in software engineering and automation, with Python as the preferred language.