Top Machine Learning Jobs in Amsterdam

Design, build, and scale reliable, low-latency systems that integrate ML models into production. Collaborate with product, data science, and business teams, lead technical design, mentor engineers, and drive adoption of tools and best practices to detect and mitigate financial crime and fraud at global scale.

The Engineering Manager leads the Optimize Interfaces team, driving architecture strategy, mentoring engineers, collaborating across teams, and fostering an inclusive culture.

Lead architecture and technical strategy for merchant fraud prevention across multiple teams. Design high-throughput, low-latency distributed systems, integrate ML/LLM models, evolve data and inference pipelines, align product and compliance goals, standardize practices, and mentor senior engineers.

As a Senior AI Research Engineer, you will drive Adyen's AI strategy, build production-grade applications, optimize AI interactions in finance, mentor teams, and engage with the AI community.

Lead the development of Adyen Protect, focusing on machine learning models for fraud detection, infrastructure scaling, and team mentorship.

Lead product vision and roadmap for agentic AI solutions, own the backlog, translate business needs into user stories, partner with data scientists and engineers, manage Agile delivery cycles, ensure responsible AI practices, and monitor model performance and continuous improvement.

Lead the AI and innovation direction for Operations, identify and prioritize high-value use cases, and build a central Ops innovation model. Manage a small Forward Deployed AI team, partner with domains and engineering to deliver scalable solutions, track delivered value, and drive adoption and upskilling across the function.

Lead organization-wide software and AI engineering strategy, design scalable cloud-native systems, drive deployment and data integration best practices, and deliver rapid prototype-to-production solutions. Own LLM and ML strategy including model fine-tuning, RAG, AI evaluation, and observability. Mentor technical leaders, shape developer experience and knowledge management, and represent engineering at executive and industry levels.

Lead global design, governance, and deployment of quantitative financial crime detection models and risk-rating engines. Translate regulatory requirements into algorithmic controls, calibrate monitoring and screening thresholds, validate models, and partner with Product, Engineering, and investigations teams to minimize false positives while maintaining detection performance. Represent model logic and tuning to regulators and banking partners.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

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 and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

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.

Lead and deliver end-to-end data science and optimization projects: develop predictive and explanatory models, design optimization/simulation solutions, process large/unstructured data, manage client relationships, supervise consultants, contribute to business development and thought leadership.

Lead and grow an internal ML engineering team, design cloud architectures, build production ML/AI solutions, guide Data Scientists to productionize models, work on client projects, deliver trainings and presentations, and contribute thought leadership (blogs, conferences).

As a Machine Learning Research Intern, you will conduct research on HFT strategies, analyze market opportunities, and collaborate on strategy implementation using ML techniques.

Join a trading team to analyze global markets and develop profitable trading strategies using machine learning and statistical models.

The Senior Quantitative Researcher will lead the development and deployment of ML-based statistical arbitrage strategies while mentoring team members and collaborating with internal teams.

Lead SAP S/4HANA Finance transformation projects: analyze and redesign finance processes, propose and implement SAP best-practice solutions (Central Finance, S/4HANA), co-create roadmaps, develop proofs-of-concept using ML, RPA and cloud, support pre-sales, training and innovation, and deliver client-facing consulting throughout full project lifecycles.

As a Data Analyst, you'll advise clients on data management strategies, implement solutions, and enhance data governance and quality. You'll also provide insights for business decisions based on analytical data evaluations.

As an Account Executive, you will manage the full sales cycle for enterprise accounts, focusing on B2B sales in the Benelux region, particularly in cybersecurity solutions. Strong communication skills and relationship-building are essential, alongside fluency in Dutch and English.

Lead and grow a backend engineering team building scalable, cloud-agnostic infrastructure and services for Databricks. Hire and develop engineers, ensure engineering excellence (architecture reviews, testing, monitoring), drive roadmaps with product leadership, and coordinate cross-team execution to deliver reliable distributed systems and ML infrastructure.

Lead strategy and delivery for knowledge management and AI in an AI-assisted research workspace. Own product vision, roadmap, and squad delivery for project spaces, personalization, and a researchers persistent memory. Run customer discovery, partner with retrieval and storage teams, work with embedded data scientists on evaluation, and turn evidence into prioritized product improvements toward an AI-maintained knowledge base.

Lead global marketing strategy and GTM to scale Aisle into a market leader. Own brand, PR, product positioning, full-funnel demand generation, ABM, marketing tech stack, RevOps, attribution, budget/agency management, and grow a multidisciplinary marketing team aligned to revenue targets.

Work with the Data & Analytics team to solve client data science and analytics problems. Apply theoretical machine-learning and statistical knowledge in practice, collaborate with Data Scientists, Engineers, and Analysts, take on project tasks, and contribute to knowledge sharing and visualization deliverables.