FittyFreak, a venture born out of a passionate vision to revolutionize the way we consume sports supplements. At FittyFreak, our commitment was to provide the highest quality isolate whey protein available in the world, boasting an unparalleled protein content without compromising on taste. Backed by scientific research, we aimed to redefine the standards of sports nutrition, setting a new benchmark in the industry.Our mission was clear - to offer a product that not only excelled in its nutritional profile but also delivered a delightful taste experience. We believed in transparency and the power of science, ensuring that every product we offered was supported by rigorous research and development.Unfortunately, despite our earnest efforts and dedication in the laboratory, we faced unforeseen challenges that hindered the realization of our ambitious vision. As an entrepreneur, I made the difficult decision to shut down FittyFreak. While the journey was cut short, the lessons learned and the commitment to excellence remain ingrained in the values that drove this startup.I want to express my gratitude to the supporters, customers, and partners who joined us on this journey. We may have closed this chapter, but the spirit of innovation and dedication that fueled FittyFreak will endure in future endeavors.

During my remote internship with Apple's "On-Device Machine Learning" team, I played a key role in optimizing algorithms for seamless integration across Apple devices—from iPhones and Macs to iPads and Apple Watches. Using Swift and Objective-C, I enhanced on-device performance, integrated machine learning models with Core ML, and conducted statistical analyses. This experience not only refined my iOS development and debugging skills but also gave me a unique perspective on advancing technologies that power user experiences across the entire Apple ecosystem. Collaborating in a remote setting, I contributed to the future of machine learning on diverse Apple devices.Contributions:- Played a crucial role in optimizing algorithms to ensure efficient on-device performance.- Integrated machine learning models with Core ML for use across various Apple devices, including iPhones, Macs, iPads, and Apple Watches.- Actively participated in the software development lifecycle, contributing to project planning and execution.- Applied statistical analysis skills to enhance the quality and effectiveness of machine learning models.- Collaborated effectively with a globally dispersed team, demonstrating adaptability in a remote work setting.- Contributed to advancing technologies that shape the future of on-device machine learning experiences across the Apple ecosystem.Learnings:- Optimized algorithms for on-device performance across a range of Apple devices.- Applied Swift and Objective-C for seamless integration of machine learning models.- Gained insights into statistical analysis techniques for data preparation and model evaluation.- Enhanced iOS app development skills with a focus on the unique challenges of on-device machine learning.- Developed proficiency in debugging tools within the Xcode environment.- Acquired a deep understanding of the software development lifecycle and industry best practices.

In my remote internship at Stripe as a "Software Engineer, Verification & Identity Platform," I applied a tech stack encompassing C++, Java, and Python to architect, develop, and maintain pivotal APIs and systems. My role involved adeptly debugging intricate production issues across the stack, showcasing my prowess in troubleshooting and system optimization. Collaborating on large-scale feature development, I contributed to the enhancement of engineering standards, tooling refinement, and process optimization. This distinctive experience allowed me to actively shape and innovate within Stripe's tech ecosystem, demonstrating fluency in languages such as C++, Java, and Python, coupled with a keen understanding of robust software engineering practices.Contributions:- Architected and developed critical APIs and systems using C++, Java, and Python within Stripe's Verification & Identity Platform.- Debugged intricate production issues across the tech stack, showcasing troubleshooting and optimization skills.- Collaborated on large-scale feature development, contributing to the enhancement of Stripe's tech ecosystem.- Actively participated in elevating engineering standards, refining tooling, and optimizing processes for increased efficiency.Learnings:- Mastered the application of C++, Java, and Python in a real-world, high-impact engineering environment.- Developed advanced troubleshooting skills through debugging complex production issues.- Gained insights into large-scale feature development and its integration into a robust tech ecosystem.- Acquired experience in refining engineering standards, tooling, and processes to meet industry best practices.