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.

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

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.

Lead authentication product strategy to reduce checkout friction and boost conversion. Own roadmap, partner with ML, engineering, design, and commercial teams to scale modern methods (passkeys, device verification), define success metrics, and roll out globally across merchants and markets.

This internship involves assisting the ServiceNow Impact Team in delivering technical accelerators for clients, improving processes, and enhancing customer adoption of ServiceNow products.

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.

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

Lead product design vision and strategy across TIDAL, driving complex initiatives end-to-end. Define design systems and standards, pioneer AI-driven approaches, partner with Product/Engineering/ML leadership, mentor designers, and identify new business opportunities to empower artists.

Develop core methods for temporal ontology extraction and contradiction detection. Collaborate with research teams and publish findings. Prototype ideas, create datasets, and validate methods.

As an AI Product Manager, you will define the product roadmap, collaborate with teams to develop AI features, conduct market research, and ensure ethical AI use.

Work on client-facing analytics projects: design solutions, build prototypes, implement ML/NLP models (e.g., PD models, decarbonization, churn, GenAI chatbots), validate results, and communicate findings to clients and colleagues across industries.

2–4 month internship within Oliver Wyman's Data & Analytics team. Work on analytics and ML projects (NLP, GenAI, credit risk, decarbonization, supply-chain risk), build prototypes, collaborate with clients and colleagues, and present insights. Gain mentorship and international exposure.

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.

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.

Lead end-to-end data science and optimization projects: build predictive and explanatory models, design operational research and Big Data solutions, manage client relationships, supervise consultants, contribute to business development, publications, training, and firm influence.

Lead client engagements designing and delivering advanced analytics and Generative AI solutions. Develop predictive/econometric/optimization/time-series models, lead LLM projects, advise stakeholders, mentor teams, support business development and thought leadership activities.

Work within multidisciplinary teams to build statistical models, optimization solutions, machine learning and Generative AI/LLM applications. Translate analytical findings into client-facing presentations, facilitate workshops, and deliver actionable insights using advanced analytics and coding skills.

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.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.