Research Scientist; Information Retrieval & Recommendation Systems

Job Description

• Research, evaluate, and adapt state-of-the-art techniques to solve large-scale AI problems.
• Fine‑tune and evaluate Transformer-based models and embedding models for domain‑specific applications.
• Contribute to research initiatives in Information Retrieval, Product Matching, Recommendation Systems, and Generative AI.
• Collaborate with technical colleagues on the integration of ML solutions.
• Contribute to scientific publications, patents, and innovation initiatives. Maintain software and data assets following high‑quality engineering standards.
• Develop and apply machine learning innovations to business problems with moderate technical supervision.
• Assess experimental results and determine their applicability to real‑world business challenges.
• Understand stakeholder requirements and communicate results and recommendations clearly and effectively.
• Perform feasibility studies and analyze data to identify appropriate technical solutions.
• Develop scalable, reproducible, and maintainable machine learning solutions.

• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Physics, or a related quantitative discipline.
• 3‑6 years of experience in Machine Learning, Deep Learning, or AI research.
• Experience with Python, PyTorch, Hugging Face, Pandas, Scikit‑learn, and Git.
• Experience training Transformer models, embeddings, and modern NLP techniques.
• Experience training custom SLMs and/or small reasoning models.
• Familiarity with Information Retrieval concepts and vector databases (e.g., FAISS, ChromaDB, Pinecone).
• Understanding of contrastive learning and representation learning techniques.
• Experience performing EDA with large datasets and writing production‑quality code.
• Ability to understand scientific papers and implement research ideas into practical solutions.
• Strong analytical, problem‑solving, and communication skills.
• Ability to work effectively within a diverse, international team.

• Publications in AI, NLP, Information Retrieval, or Recommendation Systems.
• Experience with RAG architectures, LLMs, and agent‑based frameworks.
• Experience with Lang Chain or Lang Graph.
• Experience with Knowledge Graphs.
• Experience with MLOps practices.
• Experience with Databricks, SQL, Elasticsearch.
• Experience in retail, consumer intelligence, e‑commerce, or FMCG domains.

• Salary: €46,100 up to €51,000 EUR gross per year. Performance‑based bonus may apply. Placement within the range is based on objective criteria including experience, skills, and internal equity considerations.
• Benefits: flexible working environment, volunteer time off, Linked In Learning, Employee Assistance Program (EAP).

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws.

NIQ invites individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact.