Imane User
@imaneuser1
AI engineer building production RAG systems and GenAI evaluation frameworks for reliable, high-impact outcomes.
What I'm looking for
I’m an AI Engineer focused on hands-on GenAI delivery—building RAG systems, LLM evaluation frameworks, and predictive ML models that work in production environments. I care about reliability: I validate outputs, measure quality, and iterate until models consistently meet real task requirements.
At Syensqo in Brussels, I’m currently developing an evaluation framework for GenAI systems across RAG pipelines, autonomous agents, and structured LLM outputs. I’m building systematic testing and monitoring infrastructure to support trustworthy performance over time.
Previously, I contributed to the world’s first hydrogen-powered round-the-world flight by processing 50+ technical documents and developing a RAG-based pilot assistance system for knowledge retrieval in operational contexts. I also automated 80% of travel proposal generation workflows, turning complex information into faster, usable decisions.
I’ve proven my impact through research and competitions: at the UM6P & COLAS Hackathon I designed evaluation metrics and benchmarks for RAG systems, AI agents, and structured outputs, earning 1st Place. I also achieved 62.5% accuracy on Long-Range Arena using custom attention mechanisms, and I keep pushing my curiosity through continuous learning and cross-domain collaboration.
Experience
Work history, roles, and key accomplishments
GenAI Evaluation Framework Intern
Syensqo
Mar 2026 - Present (3 months)
Developing a comprehensive evaluation framework for GenAI systems across RAG pipelines, autonomous agents, and structured LLM outputs. Building automated evaluation pipelines to assess factuality, relevance, coherence, and task completion for reliability in production.
Climate Impulse GenAI Intern
Syensqo
Jul 2025 - Sep 2025 (2 months)
Contributed to a hydrogen-powered round-the-world flight by building a RAG-based pilot assistance system that retrieves knowledge from 50+ technical documents. Developed predictive maintenance models (LSTM/Transformer) from multi-sensor data and implemented runway crack detection with a trained ConvNeXt model alongside a PowerBI operations dashboard.
Education
Degrees, certifications, and relevant coursework
Mohammed VI Polytechnic University
Engineering degree in Computer Science, Artificial Intelligence & Machine Learning
Pursuing an Engineering degree in Computer Science at Mohammed VI Polytechnic University, specializing in Artificial Intelligence & Machine Learning, expected to graduate in 2026.
Availability
Location
Authorized to work in
Portfolio
github.com/ImanefjerJob categories
Skills
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