11 дней назад
Research Scientist (GenAI/LLM)
38 400 - 46 500€
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Scientist (GenAI/LLM) (Machine Learning and Applied AI): Developing and delivering machine learning proof of concepts for large-scale data challenges with an accent on language models, generative AI, agentic AI, and process automation. Focus on feasibility studies, prompt engineering, RAG, document processing, fraud detection, and integrating maintainable ML solutions into production.
Location: Hybrid, Madrid, Spain
Salary: €38,400–€46,500 per year
Company
is a consumer intelligence company delivering retail and consumer insights through advanced analytics and data platforms across more than 100 markets.
What you will do
- Develop and apply machine learning innovations for real-world, large-scale data challenges.
- Analyze data, conduct feasibility studies, and select simple, scalable, reproducible, and maintainable ML approaches.
- Research, build, test, support, and deliver proof-of-concept solutions.
- Communicate requirements, results, and conclusions clearly to technical colleagues and business stakeholders.
- Collaborate on the integration and deployment of ML solutions while maintaining high-quality data and software.
Requirements
- Bachelor’s degree in Computer Science, Statistics, Mathematics, or an equivalent quantitative discipline.
- At least 2–5 years of experience in a related machine learning field.
- Hands-on expertise in machine learning, NLP, LLMs, GenAI, AgenticAI, and data science.
- Practical experience with prompt engineering, RAG, document processing, fraud detection, datasets, ML models, and evaluations.
- Experience with Python, PyTorch, Git, pandas, Dask, Polars, scikit-learn, Hugging Face, Docker, and Databricks.
- High-level English communication skills, analytical thinking, problem-solving ability, and the ability to meet deadlines.
Nice to have
- Master’s or PhD in AI/ML with published papers.
- Experience with large datasets, production-grade code, and operationalizing ML solutions.
- Experience with tabular data, anomaly detection, time-series forecasting, and automated classification.
- Experience with MLOps tools such as MLflow and Prefect, and deploying AI/ML solutions to Azure or other cloud platforms.
- Experience in retail, consumer, ecommerce, business, or FMCG products.
Culture & Benefits
- Flexible working environment.
- Volunteer time off.
- LinkedIn Learning access.
- Employee Assistance Program.
- Inclusive culture with international colleagues and a focus on diversity, equity, and inclusion.
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