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I'm Shah Abedinn, an AI Engineer and Machine Learning Developer with 3+ years of experience building and deploying production-ready AI systems and automation workflows that integrate directly into business operations. I design AI-driven agents that ingest data from multiple sources, apply scoring logic and ML models, and trigger automated actions through APIs. I translate unstructured and semi-structured data into actionable signals using Python, NLP, and Generative AI (LLMs), and I build end-to-end ML pipelines covering data ingestion, feature engineering, model evaluation, deployment, and monitoring. I have a track record of delivering measurable business impact through automation and intelligent decision systems, and I enjoy collaborating with non-technical stakeholders to ensure AI solutions align with real-world requirements and deliver tangible outcomes.…I'm Shah Abedinn, an AI Engineer and Machine Learning Developer with 3+ years of experience building and deploying production-ready AI systems and automation workflows that integrate directly into business operations. I design AI-driven agents that ingest data from multiple sources, apply scoring logic and ML models, and trigger automated actions through APIs. I translate unstructured and semi-structured data into actionable signals using Python, NLP, and Generative AI (LLMs), and I build end-to-end ML pipelines covering data ingestion, feature engineering, model evaluation, deployment, and monitoring. I have a track record of delivering measurable business impact through automation and intelligent decision systems, and I enjoy collaborating with non-technical stakeholders to ensure AI solutions align with real-world requirements and deliver tangible outcomes.

Shah Abedinn

AI Engineer, Data Scientist, Data Analyst, +3

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I'm Shah Abedinn, an AI Engineer and Machine Learning Developer with 3+ years of experience building and deploying production-ready AI systems and automation workflows that integrate directly into business operations. I design AI-driven agents that ingest data from multiple sources, apply scoring logic and ML models, and trigger automated actions through APIs. I translate unstructured and semi-structured data into actionable signals using Python, NLP, and Generative AI (LLMs), and I build end-to-end ML pipelines covering data ingestion, feature engineering, model evaluation, deployment, and monitoring. I have a track record of delivering measurable business impact through automation and intelligent decision systems, and I enjoy collaborating with non-technical stakeholders to ensure AI solutions align with real-world requirements and deliver tangible outcomes.…I'm Shah Abedinn, an AI Engineer and Machine Learning Developer with 3+ years of experience building and deploying production-ready AI systems and automation workflows that integrate directly into business operations. I design AI-driven agents that ingest data from multiple sources, apply scoring logic and ML models, and trigger automated actions through APIs. I translate unstructured and semi-structured data into actionable signals using Python, NLP, and Generative AI (LLMs), and I build end-to-end ML pipelines covering data ingestion, feature engineering, model evaluation, deployment, and monitoring. I have a track record of delivering measurable business impact through automation and intelligent decision systems, and I enjoy collaborating with non-technical stakeholders to ensure AI solutions align with real-world requirements and deliver tangible outcomes.

Available to hire

I’m Shah Abedinn, an AI Engineer and Machine Learning Developer with 3+ years of experience building and deploying production-ready AI systems and automation workflows that integrate directly into business operations. I design AI-driven agents that ingest data from multiple sources, apply scoring logic and ML models, and trigger automated actions through APIs. I translate unstructured and semi-structured data into actionable signals using Python, NLP, and Generative AI (LLMs), and I build end-to-end ML pipelines covering data ingestion, feature engineering, model evaluation, deployment, and monitoring.

I have a track record of delivering measurable business impact through automation and intelligent decision systems, and I enjoy collaborating with non-technical stakeholders to ensure AI solutions align with real-world requirements and deliver tangible outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Research Assistant at Simon Fraser University (SFU)

January 1, 2021 - Present

Built and validated ML models in MATLAB and Python (Pandas, Scikit-learn) using sensor and operational data to predict condenser performance, improving system efficiency by 8% for the City of Burnaby. Also contributed to model validation and deployment tasks.

Machine Learning Developer at Simon Fraser University (SFU)

August 1, 2021 - December 1, 2024

Built ML models in Python and TensorFlow for early anomaly detection, improving maintenance efficiency by 20%. Automated structuring of unstructured log sheets using Python, Scala, LLMs (HuggingFace) and Raspberry Pi, reducing manual review time by 40%. Developed a TensorFlow convolutional model for real-time cloud monitoring, boosting inference speed by 18%.

Machine Learning Engineer at Mapna

June 1, 2019 - December 1, 2020

Developed and deployed predictive fault-detection models in Python using TensorFlow and scikit-learn on turbine sensor data, improving model accuracy by 15% and reducing unplanned downtime by 10%. Built real-time IoT data pipelines using FastAPI and Pandas to ingest and process streaming sensor data, enabling automated anomaly detection and low-latency inference. Developed a Docker-based experimental environment that used multi-sensor turbine data and ML models to simulate turbine behavior, leading to a 12% improvement in model accuracy.

Data Scientist at Mapna

February 1, 2018 - May 1, 2019

Developed Spark-based statistical models using SQL pipelines to analyze turbine sensor data, increasing energy yield by 2% while cutting data preprocessing latency by 40%.