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Machine Learning Engineer focused on turning NLP and generative AI research into practical, measurable products. Delivered an end-to-end RAG document Q&A system with strong human-evaluated relevance, and built systems for misinformation detection and efficient satellite-image modeling. Experience includes designing ETL and ML pipelines on AWS with monitoring and deployment, leveraging FastAPI/Streamlit, and improving dataset quality through LLM-based enrichment. Previously researched applied mathematics and taught undergraduate mathematics, strengthening a rigorous approach to analysis and problem solving.…Machine Learning Engineer focused on turning NLP and generative AI research into practical, measurable products. Delivered an end-to-end RAG document Q&A system with strong human-evaluated relevance, and built systems for misinformation detection and efficient satellite-image modeling. Experience includes designing ETL and ML pipelines on AWS with monitoring and deployment, leveraging FastAPI/Streamlit, and improving dataset quality through LLM-based enrichment. Previously researched applied mathematics and taught undergraduate mathematics, strengthening a rigorous approach to analysis and problem solving.

sadoughianzadeh reza

AI Engineer, Data Scientist, Data Engineer, +1

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Machine Learning Engineer focused on turning NLP and generative AI research into practical, measurable products. Delivered an end-to-end RAG document Q&A system with strong human-evaluated relevance, and built systems for misinformation detection and efficient satellite-image modeling. Experience includes designing ETL and ML pipelines on AWS with monitoring and deployment, leveraging FastAPI/Streamlit, and improving dataset quality through LLM-based enrichment. Previously researched applied mathematics and taught undergraduate mathematics, strengthening a rigorous approach to analysis and problem solving.…Machine Learning Engineer focused on turning NLP and generative AI research into practical, measurable products. Delivered an end-to-end RAG document Q&A system with strong human-evaluated relevance, and built systems for misinformation detection and efficient satellite-image modeling. Experience includes designing ETL and ML pipelines on AWS with monitoring and deployment, leveraging FastAPI/Streamlit, and improving dataset quality through LLM-based enrichment. Previously researched applied mathematics and taught undergraduate mathematics, strengthening a rigorous approach to analysis and problem solving.

Available to hire

Machine Learning Engineer focused on turning NLP and generative AI research into practical, measurable products. Delivered an end-to-end RAG document Q&A system with strong human-evaluated relevance, and built systems for misinformation detection and efficient satellite-image modeling.

Experience includes designing ETL and ML pipelines on AWS with monitoring and deployment, leveraging FastAPI/Streamlit, and improving dataset quality through LLM-based enrichment. Previously researched applied mathematics and taught undergraduate mathematics, strengthening a rigorous approach to analysis and problem solving.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Beginner

Language

French

Fluent

Work Experience

Machine Learning Engineer at Beam Data

May 1, 2024 - Present

Developed and deployed a RAG-based document Q&A system for employee policy support. Built an end-to-end pipeline including document parsing, embedding generation with PGVector, and performance monitoring for reliability. Implemented backend and frontend using FastAPI and Streamlit deployed on AWS EC2, ensuring scalable integration. Achieved 95% response relevance on a human-evaluated sample using few-shot prompting and semantic similarity-based example selection. Estimated ~70 HR hours/month reduction by improving access to HR information while significantly improving response time.

Data Scientist at Multiverse, Canada (Remote)

July 1, 2023 - August 31, 2023

Optimized machine learning models for satellite image classification by reducing model size and computational cost while evaluating performance versus quantum-inspired approaches. Analyzed and labeled satellite image chips with atmospheric conditions using ML techniques. Produced detailed technical documentation covering methodology, implementation, and outcomes, including validation across CNN architectures.