Machine Learning Engineer

Abdullah All Tanvir

Omaha, Nebraska, USA +1-531-***-**** *****************@*****.***

linkedin.com/in/abdullah-all-tanvir github.com/tanvir097 Google Scholar Summary

Machine Learning Engineer with 4+ years of experience in model development, debugging, and system design in machine learning platform, with strong expertise in Python, C++, and C#, and SQL databases. Skilled in building scalable applications, telemetry, operational maintenance, troubleshooting production issues, performance tuning, and implementing enhancements to existing software architectures, in collaboration and growth mindset. Experienced in cloud environments

(AWS, GCP), software testing, Linux operating systems, telemetry, and full-stack API development. Background includes data engineering, machine learning, and research in computer vision, natural language processing, and Large Language Models (LLMs) Achievements: 400+ problems solved on LeetCode/Codeforces (C/C++, Python), Champion of the Intra-University Programming Contest (2017), Best Poster Award at CS Research Fair 2025, University of Nebraska at Omaha. Technical Skills

Programming Languages: Python, C, C++, C#, JavaScript Backend and Frontend Development: NodeJS, Laravel, Django, Flask, HTML, CSS Data Processing: Apache Spark, Hadoop, Pandas, NumPy, PySpark, Dask, SQL, NoSQL Software Engineering: Object-Oriented Programming (OOP), Design Patterns, Data Structures & Algorithms, Debugging, Agile/Scrum Frameworks & Tools: Flask, FastAPI, REST APIs, PyTorch, TensorFlow, Hugging Face, OpenCV, Apache TVM Compiler Cloud & DevOps: AWS, Azure, Docker, Kubernetes, Linux, Git/GitHub Version Control Systems AI, Machine Learning / Deep Learning: Machine Learning, NLP, Computer Vision, LLMs, Generative AI, MLOps Soft Skill: Problem solving, Teamwork, Reliability, Inquisitive, Time management, Supportive, Growth Mindset, Accountability, Good communication Skills Professional Experience

Data Science Intern – Nucor Corp May 2024 – Jul 2024 Norfolk, NE, USA

• Designed and deployed a modular Python backend integrated with production dashboards for real-time metal identification; built debugging workflows and optimized architecture for maintainability and scalability.

• Automated data ingestion, transformation, and visualization using Power BI and SQL, improving financial and commercial data reporting; enabled executives to make faster, data-driven decisions.

• Designed and implemented a relational data warehouse for financial, commercial, and production data storage using ER modeling, and developed automated ETL workflows to streamline data integration and reporting Machine Learning Engineer – eGeneration Ltd. Jan 2019 – Jul 2022 Dhaka, Bangladesh

• Developed and deployed a national screen reader desktop application in C# using keystroke and voice control, applying debugging and unit testing practices; improved accessibility for visually impaired users with a 20% increase in engagement.

• Built an NLP-based AI language converter using a Recurrent Neural Network, achieving 97% accuracy in pronunciation prediction and in collaboration. Containerized the solution with distributed systems and deployed it on Azure Cloud, enabling scalable, real-time accessibility and reliability.

• Built and maintained a real-time license plate recognition pipeline (YOLOv5, OpenCV) using AI, achieving 94% detection accuracy on live video streams.

• Developed facial and speaker recognition authentication microservices in Collaboration with Flask APIs, MySQL backend, JavaScript, and deployed on AWS EC2. Enabled secure registration/login with biometric verification and security.

• Developed a microservice-based image analysis system (CNN + Flask + Docker) and integated MLOps for X-ray diagnostics using C#. Designed the system for modular deployment and fault-tolerant inference in healthcare environments.

• Developed an NLP-driven AI chatbot with Flask APIs, JavaScript, and a Siamese LSTM model. Integrated with LangChain-based retrieval system and deployed on Azure Cloud, reducing response latency through caching, load balancing, and reliability.

• Implemented a Python-based data ingestion service using the Twitter API to capture real-time tweets filtered by hashtag. Built a custom workflow to parse, clean, and automatically export data into a locally generated spreadsheet (CSV/Excel) for downstream analytics.

• Implemented an automated document processing pipeline and annotation in Python to extract data from PDFs, convert them into JSON format for information retrieval, and store the results in a MySQL.

Graduate Assistant

Feature-Invariant Generative AI Solution CNN, ViT, Adversarial Training IEEE Transactions on Information Forensics and Security, 2025

• Developed a generative adversarial training pipeline using a ViT architecture to create an invariant feature representation under heavy distortion, applied to an image watermarking application.

• Achieved 98% robustness to common distortions(cropping, resizing, compression) while preservingwatermarkimperceptibility,leveraging adversarial techniques for feature invariance.

Multimodal LLM Models Llama, Mistral, GPT-4, FastAPI IEEE Transactions on AI, 2025

• Designed and trained a multi-component LLM framework consisting of Prompting, Marking, and Detecting to generate and detect watermarked text using transformer-based models like LLaMA, Mistral and GPT-4.

• Applied multi-modal learning techniques and performed both pre-training and fine-tuning using LoRA on transformer architectures to align system instructions, user prompts, and model outputs across the three LLM modules for robust watermark generation and detection. Customer Recommendation System to Optimize Revenue Feature EngineeringPython, Pandas, Scikit-learn, SQL Heliyon. 2023 Apr 1;9(4)

• Developed a recommendation system to optimize customer engagement and pricing revenue by analyzing purchasing patterns and generating personalized product recommendations.

• PerformedExploratoryDataAnalysis(EDA) to identifykeycustomerbehaviors,trends, and correlationsintransactionaldata, leading to improved recommendation accuracy.

Education

University of Nebraska at Omaha Omaha, NE, USA

Ph.D. in Computer Science (Expected 2026) Coursework: Graph Theory, Algorithms, Software Engineering 2022 – 2026 United International University Dhaka, Bangladesh

MS in Computer Science; Key Coursework: Deep Learning, Advance AI, Data Mining Jan 2020 – Jul 2022 East West University Dhaka, Bangladesh

BS in Computer Science Coursework: Data Structures, Web Programming, Operating Systems, Fundamental AI 2015 – 2018

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