Nadir Trapsida
Applied Ml Engineer @Isaac Instruments
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WORK HISTORY
Applied Ml Engineer @Isaac Instruments
Montreal, QC, CA
Reduced AI inference latency by 50%(0.08s → 0.04s, 150k+ requests/day) by optimizing model serving and API architecture, cutting avg request time from 0.15s → 0.1s.• Brought a large-scale video analytics service to production by designing an end-to-end pipeline that processed 7k+ videos/hour through 20 ML models, with integrated monitoring and resource-efficient scheduling for reliability and scalability.• Accelerated dataset creation across multiple teams by developing an internal image/video annotation tool, improving labeling throughput and review efficiency.• Delivered a safety-event application used by major Canadian and US fleets by building the FastAPI backend and contributing to the Next.js frontend, giving clients real-time access to safety insights.• Improved internal knowledge access by prototyping a RAG-based document search chatbot with hybrid BM25 and vector search.
EDUCATION
Université de Sherbrooke
Master's degree, Artificial Intelligence
Université de Sherbrooke
Bachelor's degree, Computer Engineering
Université de Sherbrooke
Preparatory Certificate for Undergraduate Programs in Engineering, Science and Health, Computer Engineering
Lycée Enoch Olinga
Baccalauréat, Sciences with mathematics specialisation
ABOUT NADIR TRAPSIDA
I\'m an AI/ML Engineer with a background in computer engineering and electronics. I specialize in bringing machine learning models into production, ensuring they deliver real-world value. Driven by curiosity and a constant desire to learn, I’m committed to building scalable AI systems that address complex challenges. My goal is to leverage my expertise to develop production-ready models that make a meaningful impact in the field.
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