Top Machine Learning Jobs in Amsterdam

As a Machine Learning Engineer I, you will build and scale systems for ML model training, deployment, and monitoring within the payments platform, contributing to fraud detection and payment optimization.

As a Senior Data Scientist at Chaos Labs, you'll enhance modeling capabilities and deliver insights for decentralized finance, collaborating with engineering and product teams.

Lead the AI compiler team to develop compilers for NextSilicon's platforms, leveraging expertise in large-scale compiler development and machine learning.

As a Machine Learning Data Scientist, you will build scalable data products, apply ML techniques, and collaborate with various teams to deliver insights and improve the user experience.

As an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

As a Senior Solutions Consultant, act as a trusted advisor to financial institutions, managing RFPs, delivering demos, and translating business needs into solutions.

Design and deploy intelligent systems, productionize models, collaborate with stakeholders, and develop tools for cloud-based Machine Learning platform.

As a Machine Learning Engineer, you will design, deploy, and monitor intelligent systems, collaborating with stakeholders to deliver impactful solutions. You'll work on projects including demand forecasting, fraud detection, and recommendation systems using high-quality data.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

The Senior Infrastructure Engineer will deploy, scale, and maintain services for the ML/AI team, collaborating closely with ML Engineers and Data Scientists.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

Seeking a seasoned data scientist to advance methodologies for cardiovascular health assessment, collaborating with medical experts and algorithmic team.

As a Senior Geospatial Machine Learning Engineer, you will develop and improve algorithms for vegetation analysis, enhance existing products, and lead projects impacting wildfire risk management.

As a Machine Learning Engineer, you will lead a data team, develop AI products, and work with clients on ML solutions, emphasizing project and time management skills.

The Applied AI Engineer will onboard clients on Mistral AI products, manage complex integrations, and drive technological transformations through collaboration with stakeholders.

Lead and manage an engineering team in the Growth area, ensuring development opportunities, stakeholder coordination, and supporting engineering goals while fostering engineering excellence.

Lead and manage AI certification schemes globally, provide accreditation expertise, support policy rollouts, and mentor personnel in AI and information security.

The Senior ML Engineer will enhance fine-tuning methodologies, research inference optimization techniques, and re-implement LLM architectures focusing on distributed training and efficiency.

Drive development of AI/ML-powered features, integrate with ecosystems, build APIs and UIs, and enhance developer experience at ClickHouse.

The ML/AI Engineer will benchmark GPU platforms for AI workloads, analyze GPU performance, optimize ML workloads, and develop performance visualization tools.

Research and implement physics-informed AI algorithms, design workflows, supervise teams, collaborate with external institutes, and publish findings.

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

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.

The Machine Learning Platform Engineer will manage cloud infrastructure, support AI researchers, and deploy models in production, focusing on MLOps and CI/CD practices.

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