Badr Eddine
Verified Expert in Engineering
Data Scientist and Developer
Luxembourg City, Luxembourg
Toptal member since June 20, 2022
Badr is a machine learning engineer focused on search, ranking, and applied LLMs, with 6+ years and an Oxford MSc (distinction). He has shipped 5+ production learning-to-rank models for eCommerce search, contributing 9-figure incremental revenue, and co-authored a cascade-ranking paper at The Web Conf (ACM 2025). He builds reliable generative AI: production RAG with evaluation and faithfulness checks. Badr takes on relevance audits, RAG reliability work, and moving prototypes to production.
Portfolio
Experience
- Machine Learning - 8 years
- Learning to Rank - 6 years
- Information Retrieval - 6 years
- Generative Artificial Intelligence (GenAI) - 3 years
- Large Language Models (LLMs) - 3 years
- Embeddings from Language Models (ELMo) - 3 years
- Retrieval-augmented Generation (RAG) - 2 years
- Search Engines - 2 years
Work Experience
Applied Scientist, Core Search Ranking & Relevance
Amazon
- Shipped multiple production learning-to-rank models (gradient-boosted and neural) for large-scale product search, owning offline evaluation (NDCG, MRR) and online A/B experiments.
- Designed a cost-efficient cascade ranking, pairing a lightweight first-stage ranker with LLM re-ranking to cut inference cost while preserving relevance.
- Built embeddings and LLM systems that reason over catalog text to improve search quality and flag low-quality or abusive listings.
Co-founder, Applied Scientist | Engineer
UnchartedCareer
- Built the candidate-to-job matching engine: OCR resume parsing, semantic matching with embeddings, and an LLM-based fit-scorer and re-ranker conditioned on each candidate's CV.
- Shipped a real-time AI mock-interview feature with live voice (OpenAI Realtime), on-camera body-language feedback (Gemini Vision), and instant scoring.
- Grew the product to 95 paying subscribers on a two-person team, owning the full AI stack: Next.js, FastAPI, OpenAI and Gemini, and GCP Cloud Run.
Project History
Ranking Model for Media Category for an eCommerce Store
LetzPass - Production RAG with a Faithfulness and Evaluation Layer
http://www.letzpass.comUnchartedCareer - AI Job-matching and Live Interview Simulation
https://www.unchartedcareer.comEducation
Master of Science Degree in Applied Mathematics
University of Oxford - Oxford, United Kingdom
Master of Engineering Degree in Computer Science and Applied Mathematics
University of Paris-Saclay, CentraleSupélec - Paris, France
Certifications
Oxford MSc Diploma
University of Oxford
Skills
Libraries/APIs
PyTorch, XGBoost, Pandas, Node.js, Beautiful Soup, React, REST APIs, Stripe, PySpark, TensorFlow
Tools
Claude Code, Git, ChatGPT, Amazon SageMaker, Pytest
Languages
Python, SQL, TypeScript, R, Bash
Frameworks
Agentic Frameworks, LangGraph
Paradigms
ETL, DevOps, Model Context Protocol (MCP), Automated Testing, Machine-learned Ranking (MLR)
Storage
MySQL, Data Pipelines
Platforms
Amazon Web Services (AWS), Docker, Linux, Kubeflow
Other
Machine Learning, Rankings, Search Engines, Mathematics, Optimization, Graphical Models, Probability Theory, Statistics, Learning to Rank, Data Science, Data Engineering, Data Scientist, Large Language Models (LLMs), Information Retrieval, Retrieval-augmented Generation (RAG), Generative Artificial Intelligence (GenAI), Natural Language Processing (NLP), A/B Testing, Agentic AI, Regression, Web Scraping, Data Analytics, Data Preprocessing, Statistical Analysis, Large Data Sets, Artificial Intelligence (AI), Applied AI, Linear Regression, Data Analysis, Optical Character Recognition (OCR), Software Engineering, Analytics, Agentic AI Systems, Agentic Workflow Design, Machine Learning Operations (MLOps), AI Agents, LLM Agents, AI Workflow, Deep Learning, Algorithms, Data Structures, Recommendation Systems, Embeddings from Language Models (ELMo), Semantic Search, Prompt Engineering, Agentic RAG Systems, RAG Pipelines, Vector Databases, LangChain, Knowledge Graphs, Bayesian Statistics, Fine-tuning, LoRa, Feasibility Studies, AI Voice Agents, Large Language Model Operations (LLMOps), Distributed Systems, Technology, Strategy, RAG Systems, Engines, Conversational AI, Knowledge Bases, Scripting, Applied Mathematics, FastAPI, Model Evaluation, CI/CD Pipelines, Learning to Rank (LTR)
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