Senior Research Scientist (Machine Learning, NLP, Generative AI)

apartmentNielsenIQ placeBarcelona calendar_month17/6/26

Experteer Overview

In this role you will lead and apply state-of-the-art ML techniques to large-scale AI problems within recommender systems and NLP. You will collaborate with cross-functional teams to translate business needs into research-driven solutions and demonstrate impact from concept to adoption.

The position emphasizes scientific rigor, publication activity, and mentoring, while shaping AI strategy for global initiatives. You will work in a collaborative, growth‑minded environment focused on responsible and scalable AI in consumer intelligence.

Compensaciones / Beneficios

Research, evaluate, and adapt state-of-the-art techniques for large-scale AI problems
Lead development and application of ML innovations to complex business challenges with minimal supervision
Drive innovation in Information Retrieval, Product Matching, Recommendation Systems, NLP, and Generative AI
Assess emerging research applicability and identify adoption opportunities across initiatives
Design and conduct advanced experiments and feasibility studies to guide technical strategy
Develop scalable, reproducible, and maintainable ML solutions and research frameworks
Collaborate with Applied AI and Engineering teams to enable adoption of research outcomes
Mentor and support other scientists and contribute to technical growth
Lead or contribute to scientific publications, patents, and conference submissions
Communicate vision, findings, and strategic recommendations to stakeholders across technical and business functions
Promote engineering excellence, scientific rigor, and best practices across research initiatives

Responsabilidades

7+ years of experience in Machine Learning, Deep Learning, or AI research
Expertise in training transformer-based models for IR, Recommendation Systems, Product Matching, NLP, or related domains
Experience training custom SLMs and/or small reasoning models
Advanced experience with Python, PyTorch, Hugging Face, Pandas, Scikit-learn, and Git
Strong experience with Transformer architectures, embeddings, and representation learning
Experience with vector databases (e.g., FAISS, ChromaDB, Pinecone) and retrieval-based systems
Ability to understand, evaluate, and extend ideas from scientific literature
Strong analytical, problem-solving, stakeholder management, and communication skills
Proven ability to independently drive research initiatives from concept through adoption

Requisitos principales

Flexible working environment
Volunteer time off
LinkedIn Learning
Employee-Assistance-Program (EAP)
Home Office working model (Spain-based)
Performance-based bonus eligibility

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