Top Artificial Intelligence Jobs in Amsterdam

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.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, data processing systems, and TypeScript/React interfaces. Partner with customers and product stakeholders to model AI spend, usage, and FinOps workflows. Deliver reliable, scalable features from discovery through monitoring and iteration, use AI throughout the engineering workflow, contribute to architecture and design reviews, and mentor teammates.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Lead architecture and delivery of perception and spatial AI models from cloud training to deployment on automotive-grade SoCs. Define deployment-first architectures, convert state-of-the-art research into production pipelines, set evaluation and hardware-aware validation standards, partner across research/product/customers, remain hands-on prototyping and debugging, and hire and mentor a high-performing engineering team.

Leads large, complex AI-enabled business process projects under formal Statements of Work, ensuring delivery on time, within budget, and aligned with customer outcomes. Manages stakeholders, risks, scope, communications, governance, conflict resolution, and responsible AI considerations. Coordinates architects, consultants, partners, and specialists across technical and business disciplines. Supports executive relationships, business development, and add-on opportunities while delivering ERP, CRM, automation, and AI transformations using Microsoft platforms and comparable enterprise technologies.

Build, operate, and improve production services that deliver machine learning models within exocad’s AI Design product. Responsibilities include model serving APIs, containerized deployments, versioning, staged rollouts, rollback automation, infrastructure provisioning with Terraform and AWS, monitoring, observability, and performance tuning. The role also contributes to training and labeling infrastructure and requires collaboration across engineering, product, and global teams, including work across AWS global and China environments.

Work on strategic digital transactions projects (payments, identity, open banking). Perform analyses, stakeholder interviews, translate technical/commercial insights into roadmaps and specifications, support proposals and proposition development, and contribute to client-facing delivery within small cross-functional teams.

Evaluate and label photos, graphics, videos, stickers, designs, and AI-generated content in Dutch. Assess linguistic quality, accuracy, and cultural appropriateness; build Dutch-specific datasets for Canva AI internationalization; meet labeling targets; refine annotations based on feedback; and collaborate with global data-labeling teams to maintain consistent quality.

Own success for a portfolio of strategic enterprise customers by driving AI adoption, developing AI Success Plans, measuring ROI, managing customer health, engaging executives, identifying expansion use cases, leading cross-functional recovery plans, mentoring peers, and providing product feedback to improve value realization and Autonomous IT maturity.

Lead research and advisory on application security for enterprise applications (ERP/CRM). Produce thought leadership, client-facing insights, presentations, market analysis, and support sales. Mentor analysts, drive research agenda, improve processes, and advise CIOs on security strategy, vendor evaluation, metrics, and vulnerability testing across major vendors (SAP, Salesforce, Workday, Oracle).

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Build and operate Typeform’s internal AI Operations capability for R&D. Identify and prioritize AI opportunities, discover workflows, design and deliver AI-native solutions, and manage their lifecycle after launch. Responsibilities include improving enterprise AI tools, coordinating access and governance, evaluating reliability and security, supporting automations and agents, measuring adoption and value, and partnering with Product, Engineering, IT, InfoSec, Finance, and other teams.

Serve as a senior technical expert in Generative AI, Deep Learning, and Databricks Lakehouse architectures. Advise enterprise customers on agentic AI, reinforcement learning, fine-tuning, and production deployments. Partner with Product Management, Engineering, Sales, and Field Engineering across EMEA to drive Gen AI adoption, influence product strategy, deliver enablement, resolve escalations, and support competitive technical validations. Create thought leadership content and guide senior customer stakeholders through complex AI implementations.

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

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Owns AI model development end to end, including dataset design, supervised fine-tuning, post-training, evaluation, data pipelines, production deployment, monitoring, and iteration. The role optimizes models for latency, cost, reliability, and scale while collaborating with Go API and infrastructure teams. It also involves setting technical direction in an ambiguous environment, contributing to open source, mentoring engineers, and maintaining high engineering standards.

Design and build AI agents, automation workflows, and RAG pipelines using LLMs and vector databases. Integrate AI into marketing systems, optimize model cost/performance, and collaborate with stakeholders to deliver data-driven marketing solutions.

Lead strategic AI and experience orchestration engagements with account teams to accelerate adoption of Genesys AI capabilities. Shape AI use cases, lead workshops, influence deal strategy, support proposals/pricing, and drive sales enablement and field execution across the AI portfolio to deliver measurable customer outcomes.

Build production AI agents and integrations for Customer Success, Sales, and Operations. Translate manual workflows into high-value automations, connect LLMs with internal databases and SaaS tools, implement human approval gates and guardrails, manage reliable asynchronous integrations, and evaluate agent accuracy, hallucinations, latency, and cost. The role requires strong Python or TypeScript skills, Claude expertise, agent tool design knowledge, SaaS API experience, and effective collaboration with nontechnical teams.

Lead a company-wide transformation embedding AI and agentic workflows into Product and UX. Define the vision and roadmap, design and pilot AI-enabled product lifecycle practices, create scalable playbooks and governance, assess tools, coordinate cross-functional workstreams, measure adoption and impact, and align Product, UX, Engineering, and leadership. The role requires hands-on generative AI experience, strong product judgment, technical fluency, program execution, stakeholder management, and the ability to influence teams through ambiguity.

Develop automation and AI solutions supporting pharmaceutical clinical trials. Interpret requirements, identify workflow improvements, build proof-of-concept tools using R, Shiny, and LLM-supported coding, and mature successful prototypes into validated, documented, reusable solutions. Collaborate with statisticians, programmers, data scientists, and AI leads while ensuring testing, traceability, audit trails, version control, and compliance with regulated clinical development expectations.

Lead Cohere's policy engagement on compute infrastructure, export controls, sovereign AI, and national AI competitiveness. Monitor and analyze relevant developments, develop policy positions, engage governments and cross-functional teams, represent Cohere in public discussions, and produce policy analysis and thought leadership to inform strategic business opportunities and public-private partnerships.