Top Machine Learning Jobs in the Netherlands

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.

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.

As AI Strategy Lead, you'll manage key clients and develop AI strategies for tech scale-ups, leveraging your consulting experience and network.

Lead integration of flight supply partners, optimize booking experience, manage technical delivery, and leverage AI-driven solutions for performance improvements.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

The AI Product Manager is responsible for leading the vision and strategy of a GPU-accelerated cloud services platform, managing product roadmaps, collaborating with engineering teams, and driving growth within the P2P AI ecosystem.

The Lead Specialist will develop and operationalize a Red Teaming effort, conducting penetration tests and simulating threats while establishing frameworks and SOPs.

The Customer Success Manager will onboard and support Portuguese utility accounts, ensuring effective use of digital twin technology and driving long-term partnerships and customer satisfaction.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

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

Build and operate ML platform systems for training, evaluation, deployment, and serving of generative models. Improve reliability, scalability, performance, observability, and automation for GPU and cloud workloads. Develop internal tooling and agent-friendly workflows, collaborate with researchers and product engineers, and drive platform architecture and operational improvements.

Lead relevance evaluation and quality improvements by fine-tuning LLMs, building low-latency reranking and filtering systems, scaling LLM deployments, creating automated monitoring pipelines and agentic insights, and validating impact via A/B tests while collaborating with cross-functional teams.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

The Customer Value Architect will engage with customers to ensure the effective adoption and value realization of the Neara platform, focusing on ROI metrics and customer relationships.

Build, deploy, and maintain ML models for real-time pricing in a two-sided digital manufacturing marketplace. Develop demand/supply, cost-estimation, forecasting, and routing probability models; design training and inference pipelines on AWS; run offline experiments and monitor production models. Collaborate cross-functionally, feature-engineer geometric and historical data, and mentor mid/junior engineers to improve pricing automation and performance.

The Change Manager will lead change management activities, support stakeholder communication, assess change impact, and foster user adoption throughout project implementations.

The Machine Learning Engineer will lead teams in developing AI solutions, manage client projects, build ML products, and guide Data Scientists.

As a Machine Learning Engineer, you will lead AI product development, collaborate with diverse teams, and guide Data Scientists while fostering professional growth and facilitating client projects.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

As an ML Research Engineer, you will develop computational methods and infrastructure to enhance molecular simulations and machine learning force fields for materials discovery.

Lead end-to-end technical programs for ML infrastructure (inference, serving, efficiency, endpoints). Coordinate cross-functional teams, prioritize overlapping projects, manage timelines, budgets and scope, drive incident management and continuous improvement, and communicate status to engineering and leadership.

As a Senior Applied ML Engineer, you'll design, implement, and optimize backend systems for a media intelligence platform, integrating AI/ML workflows and ensuring system reliability and scalability.

The AI/ML Engineer role emphasizes technical leadership, project management, and client consultation, focusing on cloud solutions and system architecture. Candidates should have experience with data centers, systems architecture, and cloud technologies, aiming for innovative solutions within budget and time constraints.