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As a Data Scientist, you will play a key role in developing end-to-end solutions for AI use cases. By taking up a use case right from the start you will help our customers define and scope the problem, pick the right ML solution and technology as well as ensure implementation, integration and deployment of your solution to production. You will do so while ensuring that our internal governance processes, technical excellence and best practices are respected. You will also collaborate with other team members in knowledge sharing as well as continuously improving our way of working.
Responsibilities
- Develop AI applications using state-of-the-art (Gen)AI technology.
- Translate business requests into AI applications.
- Pilot prototypes in production processes to demonstrate their value.
- Deploy prototypes to production to obtain reliable, scalable systems.
- Present your results in a clear manner and discuss them with multi-functional project teams.
- Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), and with other AI engineers in the team (e.g.forknowledgesharing).
- PhD or Master's degree in Artificial Intelligence, Computer Science, Engineering, or a related technical field.
- Proven experience (2+ years) in AI/ML engineering with a strong focus on deploying and integrating AI
- Strong expertise in Python
- Strong knowledge of state-of-the-art AI and statistical methods
- Proven proficiency with deploying scalable AI applications to production
- Experience using LLM’s and commonly used libraries to interact with LLM’s (Langchain, Llamaindex, ...)
- Hands-on experience with Azure Cloud, and Azure Data & AI services
- Strong Expertise with version control (Git, GitHub)
- Expertise with CI/CD pipelines, and modern software development best practices
- Experience with Agentic AI frameworks (Langgraph, AutoGen, CrewAI, …) is a big plus
- Experience with MLOps tools and frameworks (g. MLflow, Kubeflow, TFX) is a big plus
- Excellent problem-solving skills.
- Collaboration: Strong interpersonal skills to work effectively with diverse stakeholders from data science, engineering, and business units.
- Excellence: Strong commitment to excellence by consistently striving for high-quality outcomes, embracing continuous improvement, and maintaining a proactive, detail-oriented approach in all tasks.
- Innovation Mindset: Willingness to explore new technologies and methodologies to drive continuous improvement.
- Resilience: Capacity to troubleshoot and resolve issues in complex changing environments while maintaining a focus on quality and user experience.
- Communication: Ability to convey complex technical concepts to non-technical audiences and provide clear documentation.
- Fluent in English + French and/or Dutch
Key Skills
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