Founder & AI Engineer
Mar 2026 · PresentLeading product direction and building the AI, backend, data, MLOps, and AWS infrastructure for a live media intelligence platform.
I’m Mobin Shahidi, a Berlin-based AI engineer with 7+ years of engineering experience. I build production AI systems, recommender systems, LLM applications, data pipelines, and full-stack products, from early ideas to reliable deployment.
Production AI Engineer with 7+ years of engineering experience, including 3+ years specializing in AI/ML and 4+ years in full-stack software development. I build end-to-end AI systems, from large-scale data pipelines and model development to cloud deployment, MLOps, and production operations.
My career started in full-stack product engineering, where I built SaaS platforms, REST APIs, databases, and university-facing production systems. Through graduate study and applied research, I moved deeper into AI, recommender systems, NLP, explainability, and information quality. Today, I focus on bridging software engineering and machine learning by turning research ideas into reliable, observable, and maintainable AI-powered products.
A concise timeline of roles verified against my public professional profiles and CV.
Leading product direction and building the AI, backend, data, MLOps, and AWS infrastructure for a live media intelligence platform.
Developed information-quality pipelines, predictive models, and a quality-aware news-domain recommender for the EU-funded Social Media for Democracy project.
Designed and delivered an automated Reddit data pipeline for research into political discussion, with structured extraction and data-quality controls.
Developed and evaluated explainable recommendation models and co-authored research on joint recommendation and explanation generation.
Owned architecture, backend development, customer workflows, licensing, deployment, and ongoing production releases for a privacy-first SaaS product.
A practical mix of AI research, production engineering, cloud operations, product thinking, and startup execution. I focus on skills that help move ideas from prototypes to reliable systems people can actually use.
Intelligent systems from models to production.
Reliable backend, frontend, and product code.
Deployable, observable, repeatable systems.
From research questions to measurable systems.
Clear product flows backed by strong engineering.
Ownership across product, users, and delivery.
Blazor
ML.NET
MS SQL Server
IIS
A Framework for Accurate Recommendations and Explanation Generation Using Multi-Task Learning
M. Mansoorizadeh, M. Shahidi, A. Nazari · 2023
Improving News Reliability in Algorithmic Newsfeeds
M. Shahidi, L. Oswald, S. Herzog, S. Lewandowsky · 2026
Exogenous Cues to Information Quality
M. Shahidi, L. Oswald, S. Herzog, S. Lewandowsky · 2026
Possible Futures: Societal Consequences of Algorithmic Design and Social Media Use
S. Banisch, Mobin Shahidi, S. Lewandowsky · 2026
Selected excerpts from professional reference letters and collaborations.
“He was one of the best students in my class… His outstanding scientific knowledge and presentation skills impressed me.”
“His critical thinking and programming abilities make him a skillful programmer who can quickly implement theory into practice.”
“He consistently impressed me with his ability to understand complex concepts… and performed at a very high level.”
“He built a Reddit data pipeline from scratch and developed a novel recommender system… demonstrating exceptional technical skill.”
A compact look at the human side of my work: presenting ideas, building in teams, and staying competitive beyond the keyboard.
A research presentation on using social-media signals to evaluate information quality in digital news environments.
A virtual graduate seminar session in Farsi, showing my academic presentation style and ability to explain AI topics clearly.
Leading on the court: teamwork, communication, and shared momentum in a very real form.
A small reminder that good teams are built through trust, warmth, and everyday shared rituals.
Second place in a PES2019 competition: strategy, focus, and competitive energy outside work.
Open to AI/ML engineering, applied research, and product-focused AI roles, especially where research needs to become reliable production software.