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Md. H
@shakilhossai797
Applied Artificial Intelligence Engineer
Bangladesch
Bengalisch, Englisch
Über mich
I am an Applied Artificial Intelligence Engineer with 5+ years of hands-on experience in Machine Learning, Deep Learning, NLP, Computer Vision, Robotics, and IoT systems. I have a proven record of delivering production-ready AI solutions.
Kompetenzen
Md. H
offline •
Durchschnittliche Antwortzeit: 1 Stunde
Meine Dienstleistungen
KI-Websites & -Software
I will build ai automation systems, n8n workflows, and ai agent apps
Automatisierungen und Agenten
I will develop n8n automation, n8n workflow, ai automation, or n8n ai agent
Portfolio
Arbeitserfahrung
Research Assistant
AMIR lab • Vollzeit
Nov 2024 - Present • 1 yr 6 mos
AI Engineer - Applied AI Systems Dec 2023-Present AMIR Lab Dhaka, Bangladesh • Built production NLP and multimodal AI pipelines for automated content analysis and evaluation workflows. • Developed transformer-based sentiment and cyberbullying detection systems integrated into realworld applications. • Designed scalable training pipelines and inference APIs using PyTorch and FastAPI. • Converted research prototypes into deployable services used by engineers and analysts
Market Research Analyst (AI-Driven Business Analytics)
Gram Ltd, Dhaka, Bangladesh • Vollzeit
Mar 2022 - Dec 2023 • 1 yr 9 mos
Market Research Analyst (AI-Driven Business Analytics) Apr 2022 – Dec 2023 Gram Ltd., Dhaka, Bangladesh • Led data-driven strategy development for the startup product “Dhopa Elo” using market and user data. • Built customer analytics pipelines and pricing optimization logic using statistical and ML methods. • Applied social media analytics and KPI-based decision systems to improve product positioning. • Increased campaign effectiveness through predictive modeling of consumer behavior and retention.
AI Data Trainer (Machine Learning Operations)
Invisible Technologies Inc. • Vollzeit
Jul 2021 - Jan 2022 • 6 mos
AI Data Trainer (Machine Learning Operations) Aug 2021 – Jan 2022 Invisible Technologies Inc. (Remote) • Prepared, cleaned, and validated large-scale datasets for DoorDash AI-driven systems. • Improved model accuracy and operational reliability via systematic data quality optimization. • Conducted quality audits and implemented semi-automated checks for annotation consistency.
