Responsibilities
- Help develop core platform features by contributing to one of several focus areas such as Data Preparation, AI & Machine Learning, Data Consumption, Data Visualization, MLOps, Platform, or AI Governance.
- Design and implement tools for integrating, transforming, and cataloging data, along with interactive environments like Jupyter notebooks, SQL workbenches, and APIs.
- Introduce new functionalities for data handling and visualization powered by large language models.
- Improve processing efficiency for large datasets and expand support for various database systems.
- Enhance developer-focused tools including notebook interfaces and SQL query environments.
- Collaborate on advanced AI capabilities ranging from statistical analysis to time series forecasting and LLM inference.
- Create next-generation features such as unified LLM APIs across providers and integration with cutting-edge machine learning models.
- Partner with research teams to prototype and implement novel machine learning techniques.
- Build intuitive experiences that enable broad access to data and drive informed decision-making.
- Improve collaborative workspaces for organizing and exploring visualizations, datasets, and dashboards.
- Design user interfaces that leverage LLMs to answer business questions and surface meaningful insights.
- Advance data visualization with high-performance charting libraries and interactive dashboards.
- Develop new types of charts and improve rendering speed and responsiveness of visual outputs.
- Strengthen dashboarding functionality to support fast, adaptable, and user-friendly experiences.
- Build backend systems to automate and track machine learning model lifecycles while enabling team collaboration.
- Create tools that streamline retraining, monitoring, and deployment of machine learning models.
- Improve collaboration mechanisms for teams involved in machine learning workflows.
- Work on scaling and securing the platform, enhancing cloud integrations, and supporting diverse data sources and processing engines.
- Optimize data processing engines for better scalability and reduced latency.
- Extend platform support to new databases and cloud infrastructure providers.
- Develop features that support AI compliance by connecting isolated systems and simplifying governance workflows.
- Build configurable systems for managing AI governance and compliance policies.
- Simplify enforcement and integration of policies across multiple systems and platforms.
Work Arrangement
Hybrid — Amsterdam, Netherlands
Other
This role can be based onsite or in a hybrid arrangement from the Amsterdam office, or fully remote within the Netherlands.
