
Job Overview
Location
Netherlands, Amsterdam; Netherlands, Remote
Job Type
Full-time
Category
Software Engineering
Date Posted
April 21, 2026
Full Job Description
đź“‹ Description
- • As a Fullstack Software Engineer - Core at Dataiku SAS, you will contribute to building the core features of Dataiku DSS (Data Science Studio), the enterprise platform for AI success that enables organizations to design, deploy, and govern analytics, machine learning, and AI agents with transparency and control.
- • Day to day, you will work within one of several engineering themes—such as Data Preparation, AI & Machine Learning, Data Consumption, Data Visualization, MLOps, Platform, or AI Governance—developing features like LLM-powered data integration tools, next-gen ML model APIs, collaborative workspaces, high-performance dashboards, automated ML lifecycle tools, scalable cloud integrations, or AI compliance systems, using a modern tech stack including Java, Python, Angular, React, Node.js, Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
- • You will join a global engineering team at Dataiku, a company trusted by leading enterprises to operationalize AI as a business performance engine, with a commitment to innovation, open source, and quality, operating from Amsterdam or fully remote within the Netherlands.
- • In this role, you will deepen your fullstack expertise, contribute to impactful AI infrastructure, collaborate with research and product teams, and grow your skills in scaling enterprise-grade platforms while working on cutting-edge technologies like LLMs, MLOps, and multi-cloud AI orchestration.
Skills & Technologies
About Dataiku SAS
Dataiku SAS provides a collaborative data science and machine learning platform enabling organizations to build, deploy, and monitor predictive analytics workflows. Founded in 2013 and headquartered in New York and Paris, the company serves global enterprises in finance, retail, pharmaceuticals, and manufacturing. Its flagship product, Dataiku DSS, offers visual data preparation, AutoML, model management, and governed MLOps, integrating with existing cloud and on-premise infrastructure. The company aims to democratize data science across technical and business teams, accelerating AI adoption while maintaining governance, transparency, and compliance.
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