Fullstack Software Engineer

Why Engineering at Dataiku? Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here. How you’ll make an impact This position is either onsite/hybrid from our Paris office or full remote from any part of France. As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes: Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs. Add new capabilities for data integration, transformation, and visualization using LLMs Optimize workflows for large-scale datasets and improve database support Strengthen developer tools like Jupyter notebooks and SQL workbenches Tech stack: Java, Python, AngularJS, Angular AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference. Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models Collaborate with research teams on innovative machine learning experiments Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS Data Consumption: build the experience that makes data accessible and actionable for everyone. Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more Create innovative interfaces that answer business questions and surface relevant insights using LLMs Tech stack: Angular, AngularJS, Java, Python Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards. Develop new chart types and optimize visualization performance Enhance dashboarding capabilities to deliver fast and flexible experiences Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration. Build tools to automate retraining, monitoring, and deployment of ML models Enhance collaboration features for ML stakeholders Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines. Optimize processing engines for scalability and latency Expand capabilities to support new databases and cloud platforms Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes. Develop customizable platforms for managing AI compliance and governance Simplify policy enforcement and integration across disparate systems Tech stack: Java, Angular, PostgreSQL What you need to be successful We’re stack agnostic, so all you need is a significant experience in software engineering, building a real product We’re hiring at all levels (junior, mid, senior) A passion for combining backend performance with exceptional frontend user experience. You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale What does the hiring process look like? Initial call with a member of our Technical Recruiting team (45min) Video call with an Engineering Team Lead (1h30) Technical Assessment to show your skills (Home Test or Live Coding) Final Interviews with our VPs of Engineering (2h) #LI-Remote #J-18808-Ljbffr