Summary

AI/ML Engineer with experience across NLP, Search, Recommendations, RAG systems and AI Agents, with a strong Data Science background. Specializing in bridging research and production, translating raw data into strategic decision-making, with a focus on MLOps and scalable ML systems using Python, PySpark and AWS. Currently near graduation in Language Technologies at the University of Turin, with hands-on experience collaborating across Italy, Germany and Iran.

Work Experience

• AI/ML Engineer Intern

  2025-08 - 2026-01
  Trivago

  AI/ML Engineer Intern in the central team, contributing to the development of scalable ML systems for unstructured data.

  • Contributed to the development of semantic search engines using embedding models to improve query-to-accommodation matching accuracy.
  • Applied Generative AI to automate the creation of accommodation descriptions and Computer Vision to assess and optimize image quality.
  • Supported the design of End-to-End ETL pipelines for unstructured data ingestion to power these ML systems.
• Researcher & Data Scientist

  2023-09 - 2025-05
  University of Turin (DeepHealth Project)

  Collaboration focused on Federated Learning and Privacy Engineering.

  • Federated Learning: Architected decentralized training workflows across hospital networks to avoid moving raw patient data.
  • Technical Liaison: Aligned clinical requirements with HPC infrastructure for industrial partners like Philips and Thales.
  • Privacy Engineering: Deployed GDPR-compliant algorithms to ensure data sovereignty within strict hospital IT environments.
• Data Scientist

  2021-03 - 2023-07
  Snapp!

  Data Scientist focusing on forecasting, algorithms, and real-time machine learning optimizations.

  • Forecasting: Developed models to balance driver supply and demand, reducing wait times by 2 minutes.
  • Algorithms: Designed dynamic pricing algorithms to maximize revenue (+3%) during high-demand periods.
  • Machine Learning: Utilized real-time data to enhance ETA prediction accuracy by 2.5%.
  • Analytics: Monitored KPIs to identify and execute optimizations that improved driver utilization and completion rates.
• Data Scientist

  2019-05 - 2021-03
  Digikala Group

  • Engineered hybrid recommendation engines (Association Rules, Collaborative Filtering) to redesign the 'Frequently Bought Together' module, boosting Average Order Value (AOV) by 5% via cross-selling.
  • Developed price optimization algorithms for Flash Sales ('Shegeftane') to automate candidate selection and discount depth, achieving ~95% sell-through without eroding margins.
  • Built robust demand forecasting pipelines (XGBoost, Prophet) capable of handling 4x traffic loads during Black Friday, reducing logistics bottlenecks by 10% and improving inventory accuracy.
  • Enhanced search relevance by integrating custom Persian NLP models for semantic matching and misspelling correction, reducing 'Zero Search Result' queries by 7%.
• Project Contributor

  2018-09 - 2019-03
  Sharif University of Technology

  • Institutional Analytics: Created robust analytical dashboards to support institutional decision-making and enhance strategic academic planning.

Education

• Master of Science in Language Technology & Digital Humanities (NLP)

  2026-06
  University of Turin
• Bachelor of Science in Computer Science

  2019-03
  Sharif University of Technology

Skills

Publications

• Identity, Toxicity, or Complexity? (EVALITA 2026)
  EVALITA 2026

  1st Place (Italian Task): Developed a Hybrid Fusion architecture combining BERT embeddings with engineered sociolinguistic features to detect reclaimed slurs; achieved SOTA F1 of 0.8981 by modeling language-specific syntactic patterns.

Languages

• English

  Full professional proficiency
• German

  Limited working proficiency
• Italian

  Elementary proficiency