Top Machine Learning Jobs in Amsterdam

The VP Engineering for ML/AI will lead and mentor a diverse team, oversee the delivery and reliability of the ML platform, manage live production systems, and drive innovative techniques in machine learning. They are charged with ensuring alignment with company goals and fostering a high-performance culture within the engineering teams.

The Machine Learning Engineer in the MLOps team will develop, deploy, and operate MLOps tooling and services, handle model training and tracking, ensure stable model deployment, and oversee infrastructure scalability while collaborating with data science teams.

As a Senior Machine Learning Scientist at Adyen, you will design, develop, and implement machine learning algorithms for various data products. This includes creating orchestration pipelines, automating experiments, and collaborating with MLOps. You are expected to stay current with machine learning advancements and apply them effectively in your work, while also leading projects from ideation to deployment.

Seeking an experienced Product Manager to lead the insights and performance management products of a Risk & Revenue optimization suite at a financial technology platform. Responsibilities include defining success metrics, building data products for merchants, and collaborating with cross-functional teams.

As a Machine Learning Engineer, you will develop large-scale distributed training pipelines, build low-latency inference systems, optimize libraries for performance, and collaborate on ML experiments, all to drive innovations in high-frequency trading.

As a Machine Learning Intern, you will work on training ML trading models, automating workflows, and improving the GPU hardware cluster. You'll receive training and mentorship while contributing to projects that advance trading strategies.

As a Staff Machine Learning Engineer at Mozilla, you will lead the development of Generative AI solutions for Firefox, collaborating with various teams to design, build, and integrate machine learning models. Your responsibilities include creating infrastructures for model training and inference, implementing validation processes, and optimizing model performance in production environments.

The Senior/Staff ML Engineer will focus on developing agentic models for software engineering tasks, working on training large language models, exploring data mining techniques, and ensuring robust infrastructure for model performance.