Nicola Cecere
Applied Scientist at Amazon, Madrid
I am an Applied Scientist at Amazon in Madrid, currently working on applied AI with a focus on AI agents, LLM safety, and Evaluation.
My research spans generative AI, uncertainty estimation, information retrieval, NLP, recommender systems, and LLM optimization, with a focus on turning research ideas into reliable real-world systems. I've published peer-reviewed work at NAACL workshops, ICLR workshops, IIR, and RecSys, and was awarded 1st place in the 2023 ACM RecSys Challenge academic leaderboard.
Previously, I earned a Double Master's Degree with Honors in Machine Learning and Data Science from Politecnico di Milano and Universidad Politecnica de Madrid through the EIT Digital program.
I'm passionate about innovation, early-stage product development, and using AI to solve real business problems.
Experience
Applied Scientist — Amazon
- Work on applied AI systems, currently focused on AI agents, LLM safety, and evaluation
- Previously worked from the Edinburgh office on large-scale ML systems for Intelligent Talent Acquisition
- Build production-grade machine learning systems with Python, Apache Spark, and AWS
Applied Scientist Intern — Amazon
- Researched uncertainty estimation and diverse generation in LLMs
- Reduced batch inference time from 24h to 2h through optimization
- First-author paper accepted at NAACL '25 and ICLR '25
Founding AI Engineer — Mosaic
- Designed scalable RAG systems for investment banking
- Built training pipelines and led document analysis research
ML Research Student — Politecnico di Milano
- Developed LLM-based recommendation algorithms
- Published two research papers including a first-author contribution
Education
M.Sc. Computer Science and Engineering
Graduated 110/110 with honors. Thesis: Leveraging LLM Embeddings to Enhance Review-Based and Traditional Recommender Systems. EIT Digital specialization in Innovation and Entrepreneurship.