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

(Note: this is a Software Engineer position, focused on developing Dataiku's MLOps features and capabilities. We have separate positions open for Data Scientist, Research Scientist or ML Engineer)

You will focus on Dataiku DSS’ MLOps capabilities, from automating the retraining, tuning, monitoring and deployment of ML models to the interfaces that allow various stakeholders, with their own skills and role, to collaborate on ML projects.

Your role will be to add new features or improve existing ones to help our customers use predictive algorithms, put them into production, and monitor them with an intuitive and user-friendly interface, as well as APIs that let coders control and automate all those operations. You may also develop features to put humans in the validation loop, or collaborate with the Governance feature team to develop cross-product features and keep bringing values to all users.

The platform itself is in Java, Python, and Scala for the backend part, with JavaScript and Angular on the frontend.

What you need to be successful

• You have a significant experience in software engineering
• You are interested in machine learning and are not afraid of statistics
• You are customer-oriented — you want to understand how the product is used and solve actual customer problems
• You know that boosted trees are not only about silviculture
• You have one or more professional experience building a real product
• You are humble and kind
• You don't hesitate to ask questions when you don't know, and you treat your colleagues with respect, kindness, and honesty

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team
• Video call with an Engineering Team Lead
• Technical Assessment to show your skills (Home Test or Live Coding)
• Debrief of your Tech Assessment with Engineering Team member
• Final Interview with a VP Engineering #LI-Hybrid