Top Machine Learning Jobs in the Netherlands

Design, build, and scale reliable, low-latency systems that integrate ML models into production. Collaborate with product, data science, and business teams, lead technical design, mentor engineers, and drive adoption of tools and best practices to detect and mitigate financial crime and fraud at global scale.

Lead product vision and roadmap for agentic AI solutions, own the backlog, translate business needs into user stories, partner with data scientists and engineers, manage Agile delivery cycles, ensure responsible AI practices, and monitor model performance and continuous improvement.

The Engineering Manager leads the Optimize Interfaces team, driving architecture strategy, mentoring engineers, collaborating across teams, and fostering an inclusive culture.

Lead architecture and technical strategy for merchant fraud prevention across multiple teams. Design high-throughput, low-latency distributed systems, integrate ML/LLM models, evolve data and inference pipelines, align product and compliance goals, standardize practices, and mentor senior engineers.

As a Senior AI Research Engineer, you will drive Adyen's AI strategy, build production-grade applications, optimize AI interactions in finance, mentor teams, and engage with the AI community.

Lead organization-wide software and AI engineering strategy, design scalable cloud-native systems, drive deployment and data integration best practices, and deliver rapid prototype-to-production solutions. Own LLM and ML strategy including model fine-tuning, RAG, AI evaluation, and observability. Mentor technical leaders, shape developer experience and knowledge management, and represent engineering at executive and industry levels.

Lead the development of Adyen Protect, focusing on machine learning models for fraud detection, infrastructure scaling, and team mentorship.

Lead the AI and innovation direction for Operations, identify and prioritize high-value use cases, and build a central Ops innovation model. Manage a small Forward Deployed AI team, partner with domains and engineering to deliver scalable solutions, track delivered value, and drive adoption and upskilling across the function.

Lead and develop globally distributed Data and AI teams to deliver production Data/AI solutions. Drive talent development, operational excellence, stakeholder alignment, and responsible AI practices while partnering with Product and Engineering to set priorities, roadmaps, and delivery metrics.

Lead global design, governance, and deployment of quantitative financial crime detection models and risk-rating engines. Translate regulatory requirements into algorithmic controls, calibrate monitoring and screening thresholds, validate models, and partner with Product, Engineering, and investigations teams to minimize false positives while maintaining detection performance. Represent model logic and tuning to regulators and banking partners.

Join Snap Inc. as a thesis student exploring efficient on-device ML for AR applications, focusing on event-driven processors. Conduct research, develop models, and produce a thesis report over 8-12 months.

Build and maintain internal web applications and tools (dashboards, search, annotation, account management) with scalable, secure front-end code. Lead projects, reduce technical debt, collaborate across time zones, and deliver well-tested, extensible solutions that explain ML outputs and improve authentication workflows.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Design and implement cloud-based data solutions and scalable data pipelines for financial services clients. Migrate legacy Excel models to Azure, support AI/ML and LLM integrations, develop data architectures, and collaborate with consultants and actuaries to productionize analytical applications while applying software engineering best practices.

Lead and deliver end-to-end data science and optimization projects: develop predictive and explanatory models, design optimization/simulation solutions, process large/unstructured data, manage client relationships, supervise consultants, contribute to business development and thought leadership.

Work with the DaVinci Engineering team to identify repetitive engineering tasks, design and pilot at least five AI use cases, evaluate impact on productivity, and recommend scaling. Activities include interviewing engineers, workflow analysis, co-creation workshops, prototyping AI solutions, and measuring adoption and outcomes.

Lead and grow the Data team to build production ML/AI solutions: design cloud architectures, deploy scalable pipelines, mentor data scientists, work on client projects, deliver trainings, and represent Sia externally.

Lead client engagements delivering advanced predictive models and Generative AI/LLM solutions. Manage stakeholders and multidisciplinary teams, mentor colleagues, contribute to business development, and represent the firm in thought leadership and internal capability building.

Collaborate in multidisciplinary teams to develop statistical models, optimization solutions, and machine learning applications. Apply Generative AI and LLMs, extract actionable insights, present results, and support client workshops to solve business problems.

Lead and grow the Data team, design cloud ML architectures, build production-grade ML/AI solutions, guide data scientists to productionize models, participate in client projects, train and mentor team members, and represent Sia externally through talks and publications.

Lead and grow an internal ML engineering team, design cloud architectures, build production ML/AI solutions, guide Data Scientists to productionize models, work on client projects, deliver trainings and presentations, and contribute thought leadership (blogs, conferences).

Drive end-to-end product development for iTero 3D imaging systems by translating clinical needs into software requirements, leading cross-functional agile teams, driving ML diagnostic initiatives from PoC to productization, analyzing clinical usage data for improvements, and embedding customer feedback into product decisions to enhance usability, performance, and clinical value.

Lead positioning, messaging, and go-to-market for FineReader and ABBYY's Document Parser/SDK. Drive developer ecosystem strategy, technical content, enablement, and GTM alignment while gathering market intelligence to inform product and growth priorities.