As a Senior Machine Learning Engineer, your mission is to help data scientists move faster and further by building the intelligence layer of our predictive agent.
You will contribute to the design of the Agent:
- the iterative process between the agent and the Data Scientist,
- the capabilities of the Agent,
- the integration of expert knowledge into the Agent,
enabling fast comparison of modeling strategies and robust evaluation across datasets and use cases.
Typical problems you will work on include real-world use cases such as churn or risk prediction, designing logic that generalizes across datasets, or structuring workflows that balance speed and methodological rigor.
You will collaborate closely with our research and engineering teams to ensure that advanced ML capabilities translate into a smooth, efficient and reliable user experience.
Role & Responsibilities
In this role, you will contribute to making advanced ML usable and effective for data scientists. You will be responsible for:
- Predictive Pipeline Design: Build and structure end-to-end expert predictive pipelines (data → model → evaluation) optimized for specific use cases.
- Agent Intelligence: Implement the decision logic that powers the agent's ability to guide, assist and automate parts of the data science workflow.
- Workflow Abstractions: Translate complex ML processes into clear, reusable abstractions that scale across datasets and problems.
- Integration with Research Outputs: Leverage models, tasks and capabilities developed by the research team, without working on core model training or synthetic data generation.
- Product Collaboration: Work closely with product and engineering to ensure ML workflows are intuitive, reliable and aligned with user needs.
- Code Quality & Reliability: Contribute clean, modular and well-tested ML code to a shared codebase used in production.
