Machine Learning Engineer

This is an opportunity to join a rapidly scaling Machine Learning Platform team building the infrastructure behind real-time machine learning products in a high-volume environment. You will work on systems that enable Data Scientists to develop, deploy, and scale models that directly influence critical business outcomes, while helping shape the future of a growing ML platform. The Company They are a global technology business operating at significant scale, processing billions of transactions and delivering products used by customers around the world. Data and machine learning are central to their strategy, with dedicated teams focused on developing intelligent, high-impact products. The organisation continues to invest heavily in platform engineering, MLOps, and AI capabilities, creating excellent opportunities for technical growth and ownership. The Role As a Senior Machine Learning Engineer, you will play a key role in developing and scaling the machine learning platform that supports multiple data science teams. Responsibilities include:

• Building, maintaining, and improving training and deployment pipelines for machine learning models
• Designing scalable infrastructure for model serving, experimentation, and monitoring
• Supporting feature store development across online and offline use cases
• Developing observability and monitoring solutions for production ML systems
• Improving model deployment and release processes
• Contributing to real-time inference systems operating at large scale
• Collaborating closely with Data Scientists to productionise machine learning solutions
• Driving engineering best practices across the ML platform
• Mentoring engineers and contributing to technical decision-making

• Strong commercial experience building production-grade software with Python
• Experience designing and operating machine learning systems in production environments
• Strong understanding of MLOps principles and the machine learning lifecycle
• Experience working with cloud platforms, preferably AWS
• Knowledge of monitoring, observability, and platform reliability practices
• Familiarity with distributed data processing technologies such as Spark or Databricks
• Experience building scalable deployment and inference solutions
• Strong communication skills and the ability to collaborate across engineering and data science teams
• Comfortable solving complex technical challenges in an evolving environment

Experience with technologies such as Python, Databricks, PySpark, XGBoost, scikit-learn, Terraform, Kafka, Triton Inference Server, DynamoDB, BigQuery, and AWS would be beneficial., If you are passionate about Machine Learning Engineering, MLOps, and building scalable production systems, apply today to discuss this opportunity in more detai

• Salary up to €110,000 depending on experience
• 10% annual bonus
• Hybrid working model with three days per week in the Amsterdam office
• Relocation support
• Visa sponsorship available
• Opportunity to work on large-scale machine learning systems with significant business impact
• Clear progression opportunities within a growing Machine Learning and Platform Engineering function