About
Highly analytical AI Engineer and Computer Science graduate with a robust foundation in Machine Learning, AI Engineering, and AI Product Management, honed through MIT and IBM professional certifications. Expertly translates complex data-driven insights into scalable AI solutions, specializing in ML systems, NLP applications, and end-to-end AI product lifecycle design. Seeking to leverage advanced technical skills and strategic AI product acumen in remote AI/ML Engineer or AI Product roles within high-growth global tech environments.
Work
IBM Certification Program
|AI Product Management Trainee
Remote, US
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Summary
Designed and managed AI product strategies from ideation to deployment, focusing on user needs, business objectives, and technical feasibility within a certification program.
Highlights
Developed comprehensive AI product strategies, aligning technical capabilities with user needs and business objectives to drive innovation and market adoption.
Established robust product lifecycle frameworks for AI-powered solutions, defining stages from ideation and validation to successful deployment and post-launch optimization.
Analyzed and balanced critical trade-offs between model performance, cost efficiency, and user experience, ensuring optimal product market fit and resource allocation.
Authored structured product documentation, including Product Requirements Documents (PRDs) and technical specifications, adhering to industry best practices and facilitating cross-functional team alignment.
Evaluated potential market impact and ROI for AI solutions, contributing to strategic decision-making processes and prioritizing features with highest business value.
IBM & MIT Training
|AI Engineer Trainee
Remote, US
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Summary
Gained hands-on experience in developing and deploying structured machine learning models for classification and prediction tasks within a remote training environment.
Highlights
Developed and implemented Python-based machine learning models, applying advanced classification and prediction algorithms to solve complex data challenges.
Executed comprehensive data preprocessing, including normalization, feature selection, and cleaning, to optimize dataset quality and enhance model accuracy by up to 15% in simulated environments.
Conducted rigorous model performance evaluation using key metrics such as accuracy, precision, recall, and F1-score, ensuring robust validation and performance tuning for various ML tasks.
Simulated scalable AI deployment scenarios, focusing on system performance optimization and integration strategies for production-level ML applications.
Contributed to the design of efficient ML workflows, reducing processing time for complex datasets by an estimated 20% through optimized code and algorithm selection.
Education
Pan-Atlantic University
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Bachelor of Science (BSc)
Computer Science
Languages
English
Certificates
AI Engineering Professional Certificate
Issued By
Massachusetts Institute of Technology (MIT)
IBM AI Engineering Professional Certificate
Issued By
Coursera (IBM)
AI Product Management Certificate
Issued By
Coursera (IBM)
Skills
Machine Learning & Artificial Intelligence
Machine Learning, Artificial Intelligence Engineering, Deep Learning, Neural Networks, Natural Language Processing (NLP), Supervised Learning, Unsupervised Learning, Model Evaluation Metrics.
Programming & Data Science
Python, SQL (Foundational), Scikit-learn, TensorFlow (Conceptual + Training Labs), Pandas, NumPy, Jupyter Notebook, Data Analysis, Feature Engineering, Data Visualization Concepts.
AI Product & System Design
AI Product Management, AI Product Strategy, System Design for AI Applications, Agile Development, Product Lifecycle Management, AI Product Lifecycle Frameworks.
Professional Skills
Problem Solving, Analytical Thinking.
Interests
AI/ML Engineering
Remote AI/ML Engineering Roles, Machine Learning Systems Design, Intelligent Automation, NLP Systems.
AI Product & Strategy
AI Product Management (Global Tech Teams), AI for Emerging Markets, Scalable Solutions.