Top Machine Learning Jobs in the Netherlands

You will build tools for ML model lifecycle, collaborating with ML Engineers to improve model deployment and monitoring. Own projects from inception to production, evaluate new technologies, and enhance the ML platform.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

As a Machine Learning Engineer, you will lead the growth of the Data team, develop AI products, and optimize ML solutions while collaborating with multidisciplinary teams on client projects.

As a Machine Learning Engineer, you will lead teams in developing AI products, work on client projects, and build production-level ML solutions while mentoring Data Scientists.

The Staff Machine Learning Engineer will design, develop, and deploy ML models, manage the ML lifecycle, mentor engineers, and integrate AI into banking platforms.

The AI/ML Engineer will design and operationalize an AI Platform using Azure, focusing on automation and improving data security while collaborating with various teams to ensure compliance and efficiency.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

As a Senior ML Researcher at JetBrains, you will train LLMs for software engineering agents, design experiments, and mentor junior colleagues.

The Senior Machine Learning Engineer will design evaluation frameworks, diagnose model performance, develop ML systems, and mentor junior engineers while collaborating across teams.

Optimize ML model training pipelines for speed and reliability, applying GPU optimization techniques and mentoring team members on performance best practices.

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.

Design, prototype, and deliver ML and LLM solutions, working closely with the Python Platform team to productionize AI workflows.

Design, build, and deploy AI-powered features for a digital asset management platform using AWS AI services and LLM APIs. Implement embedding-based search, agentic AI workflows, prototypes, and collaborate with product and engineering teams to transition prototypes into production.

Lead design, development, deployment, and monitoring of ML solutions (classifiers, regressors, ranking, LLMs). Partner with product and engineering, build reliable pipelines, improve reproducibility, and communicate model trade-offs to stakeholders.

Develop and scale neural networks for source code tasks, create and improve methods for code generation, editing, and agent-based workflows, mentor colleagues, and produce publishable ML research results.

Conduct applied AI/ML research to solve home design challenges, work with raw data, test hypotheses, and build prototypes/MVP solutions.

The intern will optimize biological AI models for efficiency, focusing on profiling bottlenecks, implementing compression techniques, and benchmarking inference pipelines.