Top Machine Learning Jobs in Amsterdam

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

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.

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.

Lead the design, development, deployment, and continuous improvement of Generative AI and machine learning capabilities. Build systems involving LLMs, multimodal models, agents, retrieval, embeddings, model adaptation, and feedback-based learning. Make architectural decisions across the ML lifecycle, optimize quality, latency, cost, and reliability, and partner with research, engineering, product, and platform teams. Mentor engineers and provide hands-on technical leadership from experimentation through production.

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.

Develop Elastic-based security and observability solutions for applications and infrastructure. Build Kibana user interfaces and REST APIs, analyze IT operations data, create Elastic and SIEM detection rules, implement Elastic Security modules, and automate zero-touch deployments with Ansible. Collaborate with customers, UI teams, product management, and IT Operations to improve monitoring, security, automation, and operational efficiency.

Lead redesign of B2B underwriting models and credit frameworks, improve data analysis and processes, support multi-country product expansion, partner with Data Science on ML models, enhance reporting and KPIs, and collaborate with cross-functional teams to steer B2B risk strategy.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Own a from-scratch rebuild of Nory's mobile app using React Native and TypeScript, ensuring reliability on low-spec devices and poor connectivity. Set architecture, design system, and migration plan, ship an MVP, integrate AI agents to speed development, and grow the codebase into a platform for cross-functional teams while maintaining high UX and reliability standards.

Lead and develop a team of Data Scientists and ML Engineers building production machine-learning systems for logistics. Drive AI adoption, roadmap prioritization, agile execution, and measurable business outcomes. Partner with Product Managers, Staff ML Engineers, and the MLOps platform team to deploy scalable solutions. The role requires deep hands-on experience with production ML, recommender systems, pricing algorithms, statistical models, and modern data and AI technologies, alongside strong people leadership and executive communication skills.

Lead Workday Compensation implementations and HCM transformations: run workshops, gather requirements, configure, test, deploy, lead workstreams, liaise with clients and teams, and apply Accenture/Workday methodologies and AI-enabled tools.

Ten-week, hands-on quantitative research internship applying mathematics, statistics and programming to market data to develop and test systematic trading strategies. Includes structured training, collaborative research projects, simulated trading, exposure to traders/researchers, and AI applications. Strong performers may receive full-time offers.

Join as a graduate quantitative researcher to design, build, test and deploy statistical and machine learning models for pricing, forecasting and signal discovery using large-scale market and unstructured data. Collaborate with researchers, traders and engineers to monitor production models, refine assumptions, and accelerate research-to-production using AI-enabled workflows.

As a Staff ML Engineer, lead the development of machine learning systems for advertising, drive strategic data decisions, optimize system performance, and mentor engineers.

Design, train, and evaluate large multimodal and vision-language-action models for robotic agents. Develop reinforcement and imitation learning methods, embodied datasets, simulation environments, world models, planning systems, and sim-to-real experiments. Build robust research software and distributed training infrastructure, validate approaches on physical robots, and collaborate with research and engineering teams to deploy reliable systems. Communicate findings through technical reports, open-source releases, demonstrations, and publications.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

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.

Develop and own production-ready machine learning, LLM, NLP, and RAG solutions within Palantir Foundry and AIP. Responsibilities include data exploration, model development, evaluation, deployment, monitoring, workflow integration, and optimization for accuracy, scalability, reliability, latency, and cost. Collaborate with engineers and business stakeholders, make architecture decisions, translate business needs into AI solutions, and communicate model behavior and limitations.

Partner with sales to discover customer needs and deliver compelling Workday Financials demonstrations, workshops, and RFP responses. Lead functional strategy in complex deals, build CFO-level relationships, support demand generation, and communicate Workdayvalue and ROI while continuously upskilling in product and AI-driven finance capabilities.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

The AI Lead is responsible for managing AI teams, driving AI project strategies, and ensuring deployment efficiency in telecommunications. They will oversee AI R&D, mentor team members, and collaborate across teams to align AI solutions with business goals.

Conduct original research in AI and machine learning, develop deep learning architectures, analyze large datasets, and explore new methodologies.

As an AI Research Intern, you will tackle AI research questions, build prototypes using AI tools, and design evaluations for AI systems while collaborating with fellow engineers and product managers.