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Maseehullah Wardak is an electrical engineering co-op student at the University of Waterloo focused on applied machine learning, AI systems, and production software development. He has built and shipped AI-powered applications spanning audio understanding, retrieval, and on-device inference. He combines strong engineering fundamentals (C++, Python, TypeScript, SQL, Verilog) with practical experience deploying models via ONNX Runtime, FastAPI, React, and cloud services. His work emphasizes measurable performance gains, efficient pipelines, and user-focused product outcomes through customer discovery and production feature delivery.…Maseehullah Wardak is an electrical engineering co-op student at the University of Waterloo focused on applied machine learning, AI systems, and production software development. He has built and shipped AI-powered applications spanning audio understanding, retrieval, and on-device inference. He combines strong engineering fundamentals (C++, Python, TypeScript, SQL, Verilog) with practical experience deploying models via ONNX Runtime, FastAPI, React, and cloud services. His work emphasizes measurable performance gains, efficient pipelines, and user-focused product outcomes through customer discovery and production feature delivery.

Maseehullah Wardak

AI Engineer, Data Scientist, Software Engineer, +2

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Maseehullah Wardak is an electrical engineering co-op student at the University of Waterloo focused on applied machine learning, AI systems, and production software development. He has built and shipped AI-powered applications spanning audio understanding, retrieval, and on-device inference. He combines strong engineering fundamentals (C++, Python, TypeScript, SQL, Verilog) with practical experience deploying models via ONNX Runtime, FastAPI, React, and cloud services. His work emphasizes measurable performance gains, efficient pipelines, and user-focused product outcomes through customer discovery and production feature delivery.…Maseehullah Wardak is an electrical engineering co-op student at the University of Waterloo focused on applied machine learning, AI systems, and production software development. He has built and shipped AI-powered applications spanning audio understanding, retrieval, and on-device inference. He combines strong engineering fundamentals (C++, Python, TypeScript, SQL, Verilog) with practical experience deploying models via ONNX Runtime, FastAPI, React, and cloud services. His work emphasizes measurable performance gains, efficient pipelines, and user-focused product outcomes through customer discovery and production feature delivery.

Available to hire

Maseehullah Wardak is an electrical engineering co-op student at the University of Waterloo focused on applied machine learning, AI systems, and production software development. He has built and shipped AI-powered applications spanning audio understanding, retrieval, and on-device inference.

He combines strong engineering fundamentals (C++, Python, TypeScript, SQL, Verilog) with practical experience deploying models via ONNX Runtime, FastAPI, React, and cloud services. His work emphasizes measurable performance gains, efficient pipelines, and user-focused product outcomes through customer discovery and production feature delivery.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Beginner

Beginner

Beginner

Beginner

Work Experience

Embedded Team Member at UWARG (University of Waterloo Aerial Robotics Group)

May 1, 2026 - Present

Developed STM32 motor-control firmware using SPI, ADC, and PWM peripherals. Integrated and validated an IST8310 magnetometer on STM32 via I2C for drone heading estimation.

Applied Machine Learning Mentee (Part-Time) at RBC Borealis

March 1, 2026 - May 1, 2026

Fine-tuned CLAP on 17.7K bird recordings for natural-language bird-call retrieval. Improved Hit@10 from 5.7% to 77.3% using balanced sampling and hard negatives. Built a bird-audio research app with text/audio search, species ID, spectrograms, and a Three.js 3D audio visualization. Reduced training time 12x by caching CLAP mel-spectrogram features as .pt sidecar files.

Software Developer Intern at Novika

January 1, 2026 - April 1, 2026

Shipped 10+ production features on an interior design B2B SaaS platform using TypeScript, React, and Supabase. Built an AI comparison tab for up to 10 materials with a chatbot and a 5-criteria scoring heatmap. Implemented 4-metric supplier analytics with SQL RPCs and event data feeding Supabase-backed dashboards. Developed a drag-and-drop React canvas with multi-page editing and Supabase cloud persistence. Conducted 25 customer discovery interviews and summarized findings with recommendations.