Top Machine Learning Jobs in the Netherlands

Develop and maintain statistical forecasts across Nutreco's global portfolio using advanced analytics and forecasting models. Improve forecast accuracy in Infor Demand Forecasting, resolve exceptions, refine segmentation and models, ensure data integrity, track KPIs (Forecast Accuracy, Bias, FVA), identify demand drivers and external data, drive continuous improvement, and communicate actionable insights to stakeholders.

Lead computational biology projects applying modeling, analytics, and AI to support manufacturing, diagnostics, and R&D in animal health. Develop, benchmark, and deliver reusable code and models (R/Python), manage project delivery and QA, communicate results to stakeholders and executives, maintain data quality and metadata, and embed analytics into business processes.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

Manage client deployments of AI-driven analytics (Emiri/Liquid AI), investigate and resolve issues, coach commercial teams, configure and QA client models, drive support process improvements, and communicate product feedback and bug reports to development.

The Senior Engineering Manager will lead teams to build scalable infrastructure for Databricks, manage talent development, and ensure engineering excellence.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

2–4 month internship within Oliver Wyman's Data & Analytics team. Work on analytics and ML projects (NLP, GenAI, credit risk, decarbonization, supply-chain risk), build prototypes, collaborate with clients and colleagues, and present insights. Gain mentorship and international exposure.

Lead data engineering and architecture efforts: triage requirements, define and enforce modelling standards (3NF, Dimensional, Data Vault), design end-to-end data warehouse and analytics architectures on cloud platforms like Snowflake, govern centralized models, guide engineering and product stakeholders, and drive adoption of scalable analytics and machine learning practices.

Design and govern enterprise-scale data architectures and models, lead data modelling standards (3NF, Dimensional, Data Vault), design end-to-end analytical and data warehousing solutions on cloud platforms (Snowflake), collaborate with product and engineering teams, and promote best practices and innovation including machine learning at scale.

Design and lead enterprise-scale data and AI architectures for global clients. Develop prototypes and proof-of-value demonstrations, govern AI agents, integrate cloud platforms and external systems, support pre-sales, establish technical standards, and mentor teams. The role requires translating business needs into secure, scalable technical solutions while driving cloud data platform adoption, data governance, modeling, and AI-driven transformation.

Lead the strategic and technical direction of LLM and agentic AI initiatives while managing and developing a high-performing team of AI engineers and researchers. Design, develop, and deploy advanced AI solutions, mentor team members, oversee performance and capacity planning, and align AI roadmaps with business objectives. Stay current with generative AI, NLP, and autonomous systems, communicate with technical and non-technical stakeholders, and champion Agile delivery practices.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Own and build Polaroid’s People Operations function, including HRIS architecture, people data, employee lifecycle processes, compliance, payroll inputs, benefits, and mobility support. Lead cross-functional projects and modernize employee services through AI automation, workflows, chatbots, and policy knowledge bases. Manage HR technology integrations, data quality, dashboards, compensation cycles, and employment-law processes across jurisdictions while partnering with Finance, IT, Legal, Payroll, and Talent Acquisition.

Develop and maintain APIs, tools, and applications using clean C# code. Design cloud-native solutions, write unit and integration tests, review and debug code, document technical designs, and contribute to AI-driven innovation. The role involves working with real estate data exchange, APIs, SSO, cloud technologies, and the full software development lifecycle in a collaborative agile team.

Leads the end-to-end development of automotive products and systems, overseeing system architecture, technical decisions, design reviews, testing, validation, risk management, budgets, and project delivery. Provides technical direction and people leadership to multidisciplinary engineering teams while collaborating with product management, manufacturing, quality, suppliers, and global engineering. Drives compliance with automotive development standards, continuous improvement, and successful delivery of hardware, software, and integrated system solutions.

Own machine learning projects from exploration through production, building reliable agentic LLM systems for clinical settings. Develop evaluation datasets, offline and online testing harnesses, LLM-as-judge workflows, regression tests, and production feedback loops. Improve models through prompting, retrieval, distillation, and fine-tuning. Partner with product, clinical, and engineering teams, while reviewing code, sharing knowledge, and mentoring junior engineers.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Lead statistical strategy and delivery for Phase I-IV clinical trials embedded with a pharmaceutical sponsor. Design analyses, support protocol and reporting activities, oversee programming/CRO work, apply SAS/R (R Shiny)/Python and ML/DL methods for analyses and automation, and mentor junior statisticians.

Lead the end-to-end search experience across platforms: define relevance and ranking strategies, partner with ML/data science, improve discovery/navigation, set search metrics, and prioritize a roadmap for UX, infrastructure, and experimentation.

Conduct a graduation research project to improve Boskalis’s machine-learning recommendations for dredging vessel operations. Review physics-informed machine learning, time-series modelling, and adaptive control methods; formulate models combining physical knowledge with data; train and evaluate improvements using historical data; assess generalization across vessels and conditions; and report reproducible findings. The intern will collaborate with data scientists and multidisciplinary engineers and use Python, version control, and Databricks.

Own the AI product vision, roadmap, prioritization, and delivery from ideation through launch. Translate business needs into technical requirements while collaborating with engineers, data scientists, marketers, and commercial teams. Drive AI adoption, monitor trends, define success KPIs, and ensure responsible, ethical, and privacy-compliant product usage.

Develop Elastic observability and security solutions for application and infrastructure teams. Build Kibana user interfaces and REST APIs, analyze IT operations data, create Elastic rules and SIEM detections, implement Elastic Security modules, and automate zero-touch deployments with Ansible. Collaborate with customers, UI teams, product management, and IT Operations while improving infrastructure automation and service quality. The role is hybrid in the Netherlands and requires Dutch nationality, a Dutch passport, and Dutch-language proficiency.