Top Artificial Intelligence Jobs in the Netherlands

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 multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

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.

Build and maintain end-to-end AI product features using LLM APIs, including chat UX and backend integrations. Design RAG and retrieval pipelines, agent orchestration, evaluation infrastructure, and scalable FastAPI/Python backends while ensuring security, privacy, and operational monitoring. Collaborate with Product, Legal Engineering, and Design to prototype and ship AI-powered legal workflows.

As an AI Engineer, you'll design AI tools for authors, enhance internal workflows, and build tools for AI development, collaborating with teams to identify AI opportunities.

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.

Design, build, and operate end-to-end AI automations and data pipelines: extract and prepare data, orchestrate LLM-based agentic workflows on Azure, integrate with systems of record, and implement evaluation, monitoring, and guardrails. Maintain Power BI reporting and semantic models, join discovery workshops to assess feasibility, and build reusable automation patterns that deliver measured business impact.

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.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.

The Director of Business Development will drive revenue through creating strategies for new business, managing client relationships, and overseeing sales processes while ensuring high service standards.

Lead and grow Enjins Investor Services: build brand and GTM, run technical AI due diligences, advise PE/VC on AI strategy, maintain investor and portfolio relationships, own product roadmap and sector alignment (climate, energy, mobility). Serve as hands-on technical lead and commercial owner of the practice.

As a Senior AI Engineer, you'll develop robust AI/ML applications for clients in Climate Tech, manage projects, and engage with business stakeholders. You'll work in small teams and support the growth of innovative solutions while enhancing your consulting skills.

Lead Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.

Review, evaluate, and annotate AI-generated text, image, audio, and video content for quality and guideline compliance. Perform quality checks, identify edge cases, contribute to dataset creation, participate in calibration activities, and provide feedback to improve annotation guidelines and workflows.

Research, train, fine-tune, and productionize speech-to-text models across 24+ European languages. Build reproducible experimentation infrastructure, design and run experiments, evaluate architectures and tooling, and own model roadmap from experiment to deployment on an in-house GPU cluster.

Design and implement scalable graph-based search services and APIs. Build backend systems using Java and Spring Boot, integrate AWS services and databases, ensure observability with New Relic and Coralogix, and champion clean code and engineering best practices while collaborating across product and engineering teams.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

The role involves evaluating AI outputs, generating content, and ensuring cultural relevance. Strong analytical skills and local insights are essential to ensure quality in AI training projects.

As a Principal Forward Deployed Engineer, you'll deploy JetBrains Central in enterprise environments, implement AI governance, mentor teams, and advise customers on AI-native development best practices.

Lead company-wide AI transformation: identify high-leverage opportunities, build and ship agentic tooling and automations, treat solutions like products, prove ROI, raise company AI fluency, and sit on the Senior Leadership Team to scale and hire a team.

Define product vision and strategy via market research and data analysis; build prioritized roadmaps; collaborate with PMs, designers, and engineers to launch products; communicate with stakeholders; track performance and iterate post-launch.

This role involves defining AI safety measures, governance patterns, and privacy guidance. You'll enhance the AI platform, ensuring safe and efficient product deployments.