Top Machine Learning Jobs in the Netherlands

Lead and deliver petrophysics, seismic petrophysics and rock physics consulting projects and training. Develop best-practice workflows, support sales with technical proposals, publish and present technical work, and build customer relationships to grow consulting services and software adoption.

Design, implement, and deploy quantitative models and algorithms for systematic trading; analyze large datasets to find trading signals; collaborate with traders and engineers to move research into production and monitor model performance in live markets.

Translate scientific research and algorithms into production-ready product features. Own end-to-end feature delivery, collaborate with users and stakeholders, work across frontend, backend, cloud, scientific computing and ML stacks, optimise performance-critical components, and leverage AI tools to improve development and delivery.

Lead AI and data science strategy and teams to design, build, and deploy ML/NLP/LLM-driven products (RAG, semantic search, embeddings). Drive evaluation, responsible AI standards, experimentation, stakeholder alignment, and measurable product and business outcomes.

As an AI Product Manager, you will define the product roadmap, collaborate with teams to develop AI features, conduct market research, and ensure ethical AI use.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Develop core methods for temporal ontology extraction and contradiction detection. Collaborate with research teams and publish findings. Prototype ideas, create datasets, and validate methods.

Work on client-facing analytics projects: design solutions, build prototypes, implement ML/NLP models (e.g., PD models, decarbonization, churn, GenAI chatbots), validate results, and communicate findings to clients and colleagues across industries.

Design, build, and deploy scalable AI/ML and Generative AI solutions for enterprise systems. Develop Python-based production applications, APIs, microservices, and MLOps/CI-CD pipelines. Implement data ingestion, preprocessing, feature engineering, model training/validation, deployment, monitoring, and lifecycle management. Collaborate with DevOps, data engineering, and product teams to ensure secure, compliant, and high-performance AI solutions.

As a Data Analyst, you will develop data strategies, enhance data governance, implement data quality processes, and provide data-related insights to clients.

Design, prototype, and deploy ML and LLM solutions using messy, real-world data. Build data pipelines, models, visualizations and PoCs. Communicate insights to technical and non-technical stakeholders and iterate quickly to deliver business impact.

The position involves conducting research and teaching in mathematics-enhanced AI for biomedical applications, mentoring students, and advancing interdisciplinary initiatives.

As the Senior Technical Lead of the AI & Analytics Ops squad, you'll drive engineering excellence, technical direction, and ensure the secure deployment and maintenance of AI workloads at scale.

Lead strategy and growth for a regional portfolio of accounting and ERP software products (Twinfield, Basecone). Define roadmap, drive AI-enabled features, prioritize investments, execute go-to-market, shape pricing and positioning, and lead a team of Product Managers across Netherlands, Belgium and the UK to deliver measurable business outcomes.

Lead global marketing strategy and GTM to scale Aisle into a market leader. Own brand, PR, product positioning, full-funnel demand generation, ABM, marketing tech stack, RevOps, attribution, budget/agency management, and grow a multidisciplinary marketing team aligned to revenue targets.

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.

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 design and productionization of ML pipelines, evaluation systems, and AI agents for cybersecurity. Own experimentation-to-production lifecycles, integrate ML across product teams, scale ML infrastructure, optimize agent performance, and mentor junior engineers while collaborating with CTO and product leadership.

Build and productionize multi-agent systems and agentic workflows for personalized e-commerce recommendations. Design agent coordination, communication, planning, evaluation, tool use, safety controls, and orchestration techniques. Address latency, cost, and reliability challenges at eBay scale while collaborating with researchers, engineers, product, design, and analytics teams. Use large multimodal datasets and A/B testing to improve marketplace outcomes.

As a Machine Learning Research Intern, you will conduct research on HFT strategies, analyze market opportunities, and collaborate on strategy implementation using ML techniques.

Join a trading team to analyze global markets and develop profitable trading strategies using machine learning and statistical models.

The Senior Quantitative Researcher will lead the development and deployment of ML-based statistical arbitrage strategies while mentoring team members and collaborating with internal teams.