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Fullstack Software Engineer - Core

Job Overview

Location

United Kingdom, London; United Kingdom, Remote

Job Type

Full-time

Category

Software Engineering

Date Posted

April 21, 2026

Full Job Description

đź“‹ Description

  • • As a Fullstack Software Engineer at Dataiku, you will contribute to building core features of the Dataiku DSS platform, working on themes such as Data Preparation, AI & Machine Learning, Data Consumption, Data Visualization, MLOps, Platform, or AI Governance, enabling enterprises to design, deploy, and govern AI at scale.
  • • Day to day, you will develop and optimize tools for data integration, transformation, and visualization; build next-gen AI features like LLM APIs and ML model deployment; enhance collaborative workspaces and dashboards; improve platform scalability and security; and work with technologies including Java, Python, Angular, React, TensorFlow, PyTorch, Kubernetes, Docker, and cloud platforms (AWS, Azure, GCP).
  • • You will join a global engineering team at Dataiku, the Platform for AI Success, which empowers leading companies to operationalize AI as a business performance engine through centralized governance and innovation across the full AI stack.
  • • In this role, you will deepen your fullstack expertise, contribute to open-source and cutting-edge AI technologies, collaborate with research and product teams, and grow your impact in a fast-paced, high-growth environment that values technical excellence, diversity, and continuous learning.

Skills & Technologies

Python
JavaScript
Java
React
Angular
Full Stack
Remote

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Dataiku SAS
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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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