Kabiir Krishna is an LLM trainer and software engineer with eight years of hands-on experience building data-driven, secure systems and AI agents. A University of Waterloo MEng graduate, he has applied ML and data engineering across cybersecurity, IoT, and geospatial domains—designing ETL and microservice pipelines, training vision and LLM models, and automating Splunk playbooks to reduce enterprise cyber risk. At PwC he developed NLP-based threat detection at scale (F1 ≈ 0.9) and expanded cloud security coverage by 120%, and at Outlier he now fine-tunes LLMs with RLHF and annotates real-world agent workflows. Equally comfortable with Python, Kafka, Docker/Kubernetes, and dashboarding (Power BI/Tableau), he blends security-first engineering with practical ML deployment experience. Notably, his background spans both research-grade model training and production automation—helping bridge the gap between prototype intelligence and operational resilience.
8 years of coding experience
2 years of employment as a software developer
Class 12th, Science, Class 12th, Science at Delhi Public School, Dwarka
Bachelor of Technology, Electronics and Communication Engineering (spl. in IoT & Sensors), Bachelor of Technology, Electronics and Communication Engineering (spl. in IoT & Sensors) at Vellore Institute of Technology
Masters, Electrical and Computer Engineering, Masters, Electrical and Computer Engineering at University of Waterloo
A repository that contains solutions for problems posted at https://projecteuler.net/
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