Applied AI Engineer

Join the CropXR Data Engineering team and help build resilient, sustainable, climate-adapted crops in an exciting collaboration between biologists, computational scientists, and software engineers.

Job description

CropXR – Data-driven support for plant resilience research. CropXR is a Dutch public-private research initiative focused on accelerating the development of climate-resilient crops. By combining biology, data science, and computational methods, CropXR develops approaches to better understand and predict crop performance under changing environmental conditions. A central component of CropXR is the Resilience Hub, a digital research infrastructure designed to integrate experimental, phenotypic, genomic, and environmental data to support data-driven crop research. Within CropXR, the MetaBuddy project aims to develop an AI-based assistant that helps researchers prepare, structure, and upload data and metadata to the Resilience Hub. MetaBuddy is intended to support researchers in converting heterogeneous inputs (including publications, metadata spreadsheets, and conversational queries) to facilitate making their data FAIR (Findable, Accessible, Interoperable, Reusable). We are seeking an Applied AI Engineer to contribute to the development of MetaBuddy. The position focuses on the algorithmic and experimental aspects of AI system development, with an emphasis on evaluating and improving methods for practical use.

This role is particularly suitable for someone who enjoys working at the interface of applied AI, scientific workflows, and interdisciplinary collaboration.

Responsibilities:

• Contribute to the core algorithmic development of MetaBuddy.
• Design and evaluate experiments involving: large language models (LLMs), retrieval-based approaches, agentic workflows, prompting strategies, and light-weight model adaptation or fine-tuning where relevant.
• Investigate how AI methods can support researchers in capturing, interpreting, and organizing metadata for submission to the Resilience Hub.
• Assess the performance of different models, workflows, and architectures for specific use cases.
• Help define technical requirements and contribute to project planning and coordination.
• Collaborate with researchers, software engineers, and external partners from different disciplines.
• Contribute to the iterative development of MetaBuddy through evaluation and user feedback.

Job requirements

We are looking for candidates with:

• Experience applying large language models (LLMs) or related AI approaches to real-world problems involving scientific or technical documents.
• Experience with structured information extraction from heterogeneous sources such as scientific publications, PDFs, spreadsheets, metadata tables, or semi-structured text.
• A solid understanding of how to design workflows for extracting, normalizing, and structuring metadata using AI methods.
• Experience assessing the quality, reliability, and accuracy of AI systems, including the design of benchmarks, evaluation datasets, and performance metrics.
• A strong understanding of the strengths and limitations of language models, including issues such as hallucinations, uncertainty, reproducibility, and robustness.
• Good programming skills, particularly in Python.
• Experience working with machine learning and LLM tooling ecosystems, including frameworks such as PyTorch, JAX, or modern LLM orchestration and evaluation frameworks.
• The ability to work independently while collaborating effectively across disciplines.
• Experience in one or more of the following areas would be considered an advantage:
• Information extraction from scientific literature, metadata standards, or document understanding pipelines.
• Retrieval-augmented generation (RAG), agentic systems, or conversational AI.
• Fine-tuning, adapting, or systematically evaluating transformer-based models.
• Benchmark design, annotation workflows, or human-in-the-loop evaluation.
• FAIR data practices or scientific data management.
• Bioinformatics, computational biology, plant sciences, or related domains.
• Working in interdisciplinary or research-oriented environments.

Applicants who do not meet every requirement but believe they are a good fit for the position are encouraged to apply. Please note: due to Dutch regulations, only candidates from EU countries or those with a valid Dutch work permit are eligible for this position.

Conditions of employment

• Duration of contract is 2 years Temporary
• A job of 38-40 hours per week.
• A salary based on Scale 10 of the CAO for Dutch Universities with a salary between €3546 - €5538 gross per month based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.

Additional information
If you would like more information about this vacancy or the selection procedure, please contact Thomas Abeel, via t.abeel@tudelft.nl.

Application procedure
Are you interested in this vacancy? Please apply no later than 28 June 2026 upload the following documents:

• CV
• Motivational letter

You can address your application to Thomas Abeel.

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.
• Please do not contact us for unsolicited services.