Türkiye
Contributing world's biggest open-source LLM frameworks to enable power and flexibility of DeepInfra.
At Sarama, a Bay Area technology startup with the ambitious goal of bridging communication between dogs and humans, I played a pivotal role as a Machine Learning Engineer. My primary responsibility was the development of a mobile application and MLOps systems capable of detecting a dog's emotions and identity using customer-provided data. This innovative application was not just a technical achievement; it represented a leap in interspecies communication, leveraging machine learning to interpret and translate canine barks into human language. My duties extended beyond development to encompass the management of data annotation jobs from scale.ai, training custom models tailored to our unique use cases, and regularly consulting with experts in the field, including our mentor, Alex Wissner-Gross. The practical application of our models was critically evaluated through our mobile app, where we monitored for any significant discrepancies in model predictions. Additionally, I was responsible for launching the app on the Play Store and Test Flight, collecting valuable analytics data, and integrating user feedback to continually refine our approach. This role was a blend of technical expertise, creative problem-solving, and a deep understanding of the nuances of animal behavior, all aimed at enhancing the bond between humans and their canine companions.
As the Chief Technology Officer and co-founder of eyeCU Vision, I spearheaded the development of innovative deep learning models for CCTV cameras, transforming them into intelligent surveillance systems. My role involved hands-on development and leading a small but skilled technical team, managing projects efficiently using Kanban sprints. A key achievement was implementing an AIoT system using NVIDIA's Jetson Nano, focusing on performance optimization in limited resource environments. Our groundbreaking work in enhancing CCTV capabilities, particularly for forest fire detection and prevention, was recognized with a significant 1M₺ grant from TÜBİTAK. This funding supported our vision of creating automated systems for early fire detection and response, showcasing a future where technology can play a crucial role in environmental safety. My role at eyeCU Vision was not just about technological innovation but also about applying these advancements for impactful, real-world applications.