Top Artificial Intelligence Jobs in the Netherlands

Leads the development of AI-powered developer productivity tools and shared ML capabilities across the software development lifecycle. Responsibilities include evaluating AI tooling, building RAG and agent systems, implementing MCP integrations, developing ML CI/CD infrastructure, defining productivity metrics, ensuring AI governance and security compliance, creating reusable prompts, and training engineering teams. The role requires hands-on technical leadership, strong MLOps expertise, production ML experience, and the ability to drive adoption across distributed teams.

Serve as the founding customer-facing engineer for Kimchi, leading product demonstrations, customer workspace setup, inference API integrations, model routing optimization, and governance policy implementation. Configure agent workflows, integrations, budgets, cost attribution, and access controls. Translate customer feedback into product improvements while identifying opportunities for revenue expansion. The role combines hands-on LLM and inference expertise with customer enablement and commercial thinking in a remote-first environment.

Lead discovery, validation, and scaling of AI-enabled products, services, and workflow transformations. Prioritize opportunities, investigate client and business challenges, guide solution concepts, and collaborate with multidisciplinary teams on prototypes and pilots. Establish success measures, implementation plans, ownership, adoption, and go-to-market strategies while aligning business, technology, domain, and leadership stakeholders.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Serve as a technical-strategic partner for AI Decisioning customers, leading use-case delivery from discovery through go-live and expansion. Collaborate with engineers, executives, marketers, and IT stakeholders to define requirements, explore customer data, recommend marketing improvements, manage project risks, and develop delivery best practices. The role also contributes to AI Decisioning product strategy and requires customer-facing consulting, strong communication, and 10–25% travel.

Build and maintain software for clinical AI medical devices across radiology modalities. Develop features, integrate systems, validate and route requests, assemble results, and support production services. Write and review code, create automated and manual tests, and own features through deployment. Ensure quality, regulatory, cybersecurity, documentation, and risk-analysis compliance while collaborating with product, service, and delivery teams.

Leads the enterprise data governance strategy, framework, roadmap, policies, standards, and data quality programs. Establishes metadata, lineage, master data, classification, access, and privacy practices while partnering with IT and Security to support secure AI initiatives. The role resolves cross-functional data issues, aligns governance with regulatory requirements, measures data quality, and develops the governance team in a regulated healthcare or technology environment.

Own a sales territory and drive new-logo acquisition from pipeline generation through closing. Partner with BDRs on account planning, build strategic client relationships, navigate complex sales cycles, influence senior decision-makers, and guide prospects as a product expert. The role requires software sales closing experience, target achievement, executive communication, entrepreneurial initiative, collaboration, and fluency in French and English.

Lead customer deployments of Kubernetes and vCluster on bare-metal GPU infrastructure, configuring GPU nodes, networking, storage, RDMA, and InfiniBand. Validate production-ready managed Kubernetes environments, troubleshoot complex infrastructure, transfer operational knowledge, document reusable deployment playbooks, and provide feedback to Engineering and Product. Support pre-sales proof-of-value engagements and help AI cloud and factory customers independently operate and scale their platforms.

Develop and maintain enterprise, cyber defence, and AI security architectures and roadmaps. Define AI security principles, controls, governance, and standards; advise stakeholders on AI risks; and guide product, engineering, DevOps, and architecture teams. Secure cloud-native AI/ML platforms, data pipelines, models, APIs, identities, and infrastructure against leakage, abuse, and adversarial threats. Represent security interests in governance boards and support secure, compliant AI adoption across the organization.

Lead the architecture and technical direction of AI compiler toolchains for heterogeneous platforms including NPUs, GPUs, vector accelerators, CPUs, and embedded systems. Translate product and customer needs into compiler requirements, interfaces, roadmaps, and implementation plans. Guide optimization, code generation, runtime integration, performance analysis, architecture reviews, and technical risk management. Collaborate with global engineering teams, customers, and partners while mentoring compiler engineers and improving engineering standards.

Lead Piano’s global marketing function across demand generation, content, messaging, product marketing, partner marketing, communications, PR, and customer events. Own qualified pipeline, new ARR, funnel economics, and market positioning. Scale demand generation, simplify complex product messaging, establish a unified platform narrative, develop partner-sourced pipeline, and lead a primarily European team. The role reports to the CEO and sits on the executive leadership team.

Manage multi-country payroll operations, compliance, audits, controls, vendor relationships, payroll analysis, and process improvements. Lead payroll system automation and scalability initiatives while ensuring accurate and timely processing across jurisdictions. Partner with finance, HR, treasury, and external providers, monitor regulatory changes, and mentor a global payroll team in a distributed technology environment.

Lead a small engineering team building and shipping AI-powered SaaS features. Set technical direction, establish standards for observability, testing, security, scalable architecture, and AI evaluation, while managing delivery timelines and team development. Remain hands-on by designing and implementing production AI systems using LLMs, embeddings, RAG, vector databases, and related tooling. Partner with Product and leadership on prioritization, architecture, resourcing, and risk management.

Lead AI enablement by identifying workflows for automation, building production-grade LLM and AI tools, driving internal adoption, and operating the supporting AWS, GitOps, CI/CD, and Kubernetes platform. Own solutions end to end from stakeholder discovery through deployment, observability, scaling, cost management, and production support.

Lead client implementations of Data and AI Governance, establishing ownership, stewardship, quality, metadata, lineage, privacy, security, and responsible AI practices. Facilitate stakeholder workshops, translate ambiguous governance challenges into practical roadmaps, embed governance into daily operations, support AI governance decisions, and create reusable templates and playbooks. Collaborate with Business, Data, AI, IT, Architecture, Privacy, and Security teams across complex enterprise environments.

Leads the global HR technology and digital transformation strategy, including the transition from Workday to SAP SuccessFactors. Oversees HR technology governance, AI adoption, automation, analytics, data quality, digital workflows, employee self-service, and enterprise transformation programs. Builds and leads a high-performing digital HR function, develops organizational capability, drives adoption, and partners with senior HR, IT, and business leaders to deliver measurable improvements in HR efficiency, employee experience, and decision-making.

Analyzes consumer, market, and social media data to measure campaign performance, identify trends, develop actionable insights, and optimize digital marketing activities. Creates reports and dashboards, supports consumer experience initiatives, collaborates with cross-functional stakeholders, and uses AI-powered tools to develop and optimize brand-consistent digital assets and social media content across EMEA.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Build and maintain PHP and Laravel backend services and APIs for a major product release. Own features from design through deployment and monitoring, integrate agentic AI workflows and LLM-based tooling, optimize performance and reliability, improve security, and mentor engineers. Collaborate independently with a cross-functional team on ambiguous technical challenges while delivering production-ready software.

Build and own production agentic AI runtime components, including context construction, retrieval and tool orchestration, ranking, scoring, guardrails, multilingual quality, latency and cost optimization, and evaluation systems. Diagnose production failures through traces and improve agent reliability for customer-facing commerce applications.

Design and optimize model-serving architectures and inference pipelines for high-throughput, low-latency AI performance on mobile, edge, and GPU-cluster environments. Develop custom GPU kernels and Metal shaders, benchmark production systems, diagnose computational and memory bottlenecks, and implement techniques including parallelism, quantization, pruning, FlashAttention, KV caching, and speculative decoding. Collaborate cross-functionally to integrate scalable inference solutions and continuously improve performance.

Conduct research and build experimental systems using LLMs, causal inference, experimentation, and optimization. Develop treatment-effect, uplift, and counterfactual models; analyze randomized trials; and create constrained optimization models for promotions and incentives. Read research papers, prototype ideas, and translate successful approaches into production systems. The internship requires collaboration in Amsterdam for 6–12 months, with at least three office days weekly.

Lead a team of researchers and engineers in developing and deploying advanced AI-driven recommender systems for eBay's eCommerce platform, leveraging ML and NLP techniques.

Lead the EMEA AI Forward Deployed Engineering team, focusing on AI transformation and building customer-facing AI applications while managing key accounts and developing team structure.