Top Machine Learning Jobs in the Netherlands

Design and govern agentic interfaces and domain architectures for AI-driven workflows across logistics, fleet, and mobility. Translate customer workflows into reusable agent skills, context and memory models, and orchestrations. Drive data-centric learning loops with data science, define integration patterns with enterprise systems, and ensure security, observability, and explainability. Own concept-to-implementation delivery and continuous improvement of domain agent capabilities in production.

The Consultant will address customer AI strategies, prototype solutions using Celonis’ technologies, and ensure successful implementation and ROI realization for AI projects.

This internship involves assisting the ServiceNow Impact Team in delivering technical accelerators for clients, improving processes, and enhancing customer adoption of ServiceNow products.

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.

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

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.

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

As an Engineering Manager, you will lead a team focused on building a machine learning-powered fraud detection engine, mentoring engineers, and collaborating across teams to achieve strategic goals.

Lead product design vision and strategy across TIDAL, driving complex initiatives end-to-end. Define design systems and standards, pioneer AI-driven approaches, partner with Product/Engineering/ML leadership, mentor designers, and identify new business opportunities to empower artists.

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.

Develop, design, test and implement imaging and 3D reconstruction algorithms using C++ and Python. Analyze real data, optimize for high-performance computing, integrate algorithms into applications, and collaborate across algorithms, physics, and electronics teams while participating in design and code reviews.

Lead end-to-end data science and statistical projects for animal health manufacturing using DOE, SPC, GLMs, multivariate analysis, simulation, predictive modeling and machine learning. Perform data quality assessments, build reproducible code and pipelines, automate workflows, support regulatory reporting, mentor colleagues, and communicate results to technical and non‑technical stakeholders while collaborating with Operations, Quality, Engineering, and Regulatory teams.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Lead vision, roadmap, and performance for Search and Cache products. Oversee product owners, align roadmap with strategy, define KPIs, collaborate with ML/Data teams, co-lead R&D and A/B testing, manage direct reports, and drive stakeholder relationships and product delivery.

Lead AI and data science strategy across ML, NLP, search, recommendation, and generative AI. Manage and develop teams to deliver production-ready systems (LLMs, RAG, semantic search, embeddings), establish evaluation and responsible AI practices, and align roadmaps with product and business outcomes while influencing senior stakeholders.

Design and deliver production-ready AI, NLP, and generative AI solutions for scientific knowledge discovery. Build LLM-powered workflows, RAG systems, retrieval/ranking/recommendation features, integrate ontologies and metadata, establish evaluation and monitoring, write production Python, and provide technical leadership and mentoring.

Lead the Recommendations engineering team to build scalable, reliable recommendation-as-a-service products. Own recommendation quality and business impact, set technical direction, translate product goals into engineering plans, ensure SLAs, hire and coach engineers, and drive system reliability and scalability.

Lead product strategy and roadmap for query interpretation and search quality. Own models, tools, and metrics to optimize recall and precision. Collaborate with ML, infra, and product teams, triage quality issues, benchmark competitors, and build evaluation frameworks and explainability for search results.

Conduct original research in AI and machine learning, develop deep learning architectures, analyze large datasets, and explore new methodologies.

The consultant will take charge of complex models, manage end-to-end projects, supervise junior consultants, and develop client relationships, primarily focusing on machine learning, operational research, and big data analysis.

Lead client engagements by developing advanced predictive models, managing stakeholders, and guiding project teams. Mentor colleagues and support business development in data science and Generative AI.

Lead client engagements in advanced analytics and Generative AI solutions, managing stakeholders and guiding teams to deliver impactful projects. Develop predictive models and offer strategic recommendations to clients, while contributing to thought leadership and business development.

The role involves leading a Data team, developing AI products, guiding Data Scientists, and collaborating in multidisciplinary projects while ensuring production-level ML solutions and training.

Intern will support the Accounting team with invoice processing, expense claims, monthly reporting, and automation projects using AI tools while contributing to finance team initiatives.

The AI Lead is responsible for managing AI teams, driving AI project strategies, and ensuring deployment efficiency in telecommunications. They will oversee AI R&D, mentor team members, and collaborate across teams to align AI solutions with business goals.