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Research Scientist (AI/ML, NLP & Information Retrieval)

External
Nielseniq logoNielseniq · Madrid, Spain
Full-timeOn-site2d ago
ComplianceDeep LearningElasticsearchGenerative AIGitHugging Face
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Benefits

Flexible working environmentVolunteer time offLinkedIn LearningEmployee-Assistance-Program (EAP)About NIQFor more information, visit NIQ.comWant to keep up with our latest updates?Follow us on: LinkedIn | Instagram | Twitter | FacebookOur commitment to Diversity, Equity, and InclusionVision insuranceFlexible scheduleEquity / stock optionsPerformance bonus

Additional Information

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. Good to Have: Publications in AI, NLP, Information Retrieval, or Recommendation Systems. Experience with RAG architectures, LLMs, and agent-based frameworks. Experience with LangChain or LangGraph. Experience with Knowledge Graphs. Experience with MLOps practices. Experience with Databricks, SQL, Elasticsearch. Experience in retail, consumer intelligence, ecommerce, or FMCG domains. Salary: €46100 up to €51000 EUR gross per year. This role might also be eligible for a performance-based bonus. Placement within the range will depend on objective criteria including experience, skills, and internal equity considerations. We are committed to equal pay and pay transparency. Remuneration decisions are made using gender-neutral and objective criteria.


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