I’m an AI Engineer and Computational Mathematics student at the University of Waterloo, with hands-on experience developing and optimizing deep learning systems at NVIDIA and in academic research. My background bridges both theoretical and applied machine learning, from designing adaptive neural decoding algorithms in Nengo to optimizing GPU-parallelized workloads in CUDA C++. I’ve contributed to projects that span computer vision, generative AI, and educational tools, and I’m deeply passionate about leveraging AI to create meaningful, human-centered experiences, especially in learning and creativity. I take pride in writing clean, efficient, and scalable code, and I’m comfortable working across the full ML lifecycle: research, experimentation, model training, and deployment on cloud environments like AWS and GCP. What sets me apart is my combination of research depth and engineering execution, I’m able to translate cutting-edge AI concepts into production-ready features that genuinely enhance user experience. I thrive in collaborative environments where innovation meets impact, and I’m excited about contributing to an AI-driven learning platform that empowers students worldwide.

Nicolas Martalog

I’m an AI Engineer and Computational Mathematics student at the University of Waterloo, with hands-on experience developing and optimizing deep learning systems at NVIDIA and in academic research. My background bridges both theoretical and applied machine learning, from designing adaptive neural decoding algorithms in Nengo to optimizing GPU-parallelized workloads in CUDA C++. I’ve contributed to projects that span computer vision, generative AI, and educational tools, and I’m deeply passionate about leveraging AI to create meaningful, human-centered experiences, especially in learning and creativity. I take pride in writing clean, efficient, and scalable code, and I’m comfortable working across the full ML lifecycle: research, experimentation, model training, and deployment on cloud environments like AWS and GCP. What sets me apart is my combination of research depth and engineering execution, I’m able to translate cutting-edge AI concepts into production-ready features that genuinely enhance user experience. I thrive in collaborative environments where innovation meets impact, and I’m excited about contributing to an AI-driven learning platform that empowers students worldwide.

Available to hire

I’m an AI Engineer and Computational Mathematics student at the University of Waterloo, with hands-on experience developing and optimizing deep learning systems at NVIDIA and in academic research. My background bridges both theoretical and applied machine learning, from designing adaptive neural decoding algorithms in Nengo to optimizing GPU-parallelized workloads in CUDA C++.

I’ve contributed to projects that span computer vision, generative AI, and educational tools, and I’m deeply passionate about leveraging AI to create meaningful, human-centered experiences, especially in learning and creativity. I take pride in writing clean, efficient, and scalable code, and I’m comfortable working across the full ML lifecycle: research, experimentation, model training, and deployment on cloud environments like AWS and GCP.

What sets me apart is my combination of research depth and engineering execution, I’m able to translate cutting-edge AI concepts into production-ready features that genuinely enhance user experience. I thrive in collaborative environments where innovation meets impact, and I’m excited about contributing to an AI-driven learning platform that empowers students worldwide.

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Experience Level

Expert
Expert
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Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Performance Engineer Intern at NVIDIA
December 1, 2024 - December 1, 2024
Developed high-performance automation tools in Python and optimized distributed ML infrastructure pipelines, reducing runtime by 45%. Contributed to scaling workloads across GPU clusters with a focus on numerics, profiling, and performance tuning for large-scale systems. Conducted quantitative analysis of ML benchmark performance to develop optimization strategies that improved runtime by 45%. Utilized GPU architecture for accelerating ML infrastructure with focus on numerics. Optimized hardware accelerators through automated processes utilizing cutting-edge optical character reading technologies, achieving accuracy exceeding 97% within testing environments.
Performance Engineer Intern at NVIDIA
December 1, 2024 - October 26, 2025
Developed high-performance automation tools in Python and optimized distributed ML infrastructure pipelines, reducing runtime by 45%. Contributed to scaling workloads across GPU clusters with a focus on numerics, profiling, and performance tuning for large-scale systems. Conducted quantitative analysis of ML benchmark performance, modeling the impact of parameters to develop optimization strategies that achieved significant runtime reductions. Leveraged GPU architectures to accelerate ML infrastructure, with emphasis on numerics. Automated processes for maintaining hardware accelerators using OCR technologies, achieving accuracy above 97% in testing environments.
Software Engineer Intern at ArcelorMittal Dofasco
December 1, 2023 - December 1, 2023
Designed and optimized REST APIs with .NET and Python, improving system efficiency by 50%. Collaborated with DevOps to automate system monitoring using Python scripting and Splunk.
Software Engineer Intern at ArcelorMittal Dofasco
December 1, 2023 - October 26, 2025
Designed and optimized REST APIs with .NET and Python, improving system efficiency by 50%. Collaborated with the DevOps team to automate system monitoring using Python scripting and Splunk.
Software Developer Intern at Autodesk
April 1, 2023 - April 1, 2023
Engineered performance-critical math nodes in C++ using linear algebra and algorithms, boosting animation workflows by 25%, with a focus on seamless user interactions. Ensured functionality, longevity and security of codebase compiler by writing comprehensive unit tests in Python and analyzed the feature space of a deep learning model, engineering new data inputs that resulted in a 34% improvement in ML infrastructure performance.
Software Developer Intern at Autodesk
April 1, 2023 - October 26, 2025
Engineered performance-critical math nodes in C++ using linear algebra and algorithms, boosting animation workflows by 25%, with focus on seamless user interactions. Wrote comprehensive Python unit tests to ensure functionality, longevity and security of the codebase; analyzed the feature space of a deep learning model and engineered new data inputs, resulting in a 34% improvement in ML infrastructure performance.
Software Developer Analyst Intern at Bank of Montreal
August 1, 2022 - August 1, 2022
Developed full-stack admin tools with JavaScript, HTML, CSS, and React for a distributed system serving 2000+ users with intuitive UI/UX design. Architected and implemented 3 C#/.NET APIs for relational databases, focusing on efficient data processing pipelines that improved data retrieval and loading speeds by 33% for downstream analysis.
Software Developer Analyst Intern at Bank of Montreal
August 1, 2022 - October 26, 2025
Developed full-stack admin tools with JavaScript, HTML, CSS, and React for a distributed system serving 2000+ users with intuitive UI/UX design. Architected and implemented 3 C#/.NET APIs for relational databases, focusing on efficient data processing pipelines that improved data retrieval and loading speeds by 33% for downstream analysis.

Education

Bachelor of Computational Mathematics at University of Waterloo
September 1, 2020 - August 1, 2025
Bachelor of Computational Mathematics with Computing Minor at University of Waterloo
September 1, 2020 - August 1, 2025

Qualifications

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Industry Experience

Software & Internet, Computers & Electronics, Manufacturing, Professional Services