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Description:

;Contributes to multiple data engineering projects. Team member in defining and builds the data pipelines that will enable faster, better, data-informed decision-making within the business. Supports the implementation of a new big data solution which supports high amounts and velocity of data and supports future growth. Works with latest developments, testing and deployment techniques to support the deployment of new releases to e.g. deploy new data pipelines and add data sources. Acts as part of a Scrum, or as a Scrum Stakeholder (e.g. Agile White belt accredited) when required.

• Supports stakeholders by gathering, analysing and modelling data & key performance indicators to develop quantitative and qualitative business insights in an agile fashion. Identifies and proposes opportunities for improved data analysis. Opinions valued within team and by project manager.

• Supports stakeholders by gathering, analysing and modelling data and key performance indicators of moderate complexity. Working as part of a Team to develop and deploy innovative big data platforms for advanced analytics and data processing.

• Works under direct supervision of Manager / Team Lead for moderately complex activities; broad guidance on operational activities.

This job profile contains generic information and does not describe individual positions or required job competencies. Grading decisions will also depend on other factors.

Requirements:
- Master’s or Ph.D. degree in computer science, engineering, mathematics, theoretical science, statistics, or related scientific field
- 3+ years of experience with deep learning frameworks such as PyTorch or TensorFlow.
- 3+ years of theoretical and hands-on experience in deep learning and computer vision
- Theoretical and hands-on track record of experience working with the latest of Generative modeling for computer vision applications (VAEs, Diffusion Models, Flow Matching, etc.)
- Theoretical and hands-on track record of experience working with (Multi)Agentic AI tech stacks including LLMs, VLMs, etc.
- Proven examples of implementing experimental pipelines and prototyping Generative AI applications using LLMs and VLMs
- A mathematical background covering some subset of linear algebra, probability, multivariate calculus, geometry, and/or numerical methods
- Affinity with lifecycle and data management, and experience using Git to manage models, and source code
- Excellent coding skills in Python, and software development.
- Experience with cloud stacks and architectures, such as Azure, AWS, etc. Comfort with some flavor of Unix shell environment (e.g., bash)
- Must have legal authorization to work in Netherlands on a full-time basis for anyone other than current employer
- Publications in flagship venues of AI or related scientific journals or conferences is a plus
- Experience as a technical lead in Generative AI and computer vision projects is a plus