Michael S. Email & Phone Number

Remote

With My client T-Mobile, I improve the release and deadlines of various mobile apps for T-Mobile customers.

Texas, United States

Product Owner for BCBS mobile applicationLed the development and launch of new mobile app features, improving customer access to insurance benefits and cost transparency.Collaborated with cross-functional teams to implement new disability requirements, enhancing inclusivity for diverse user needs.Drove the redesign of the user interface (UI), resulting in a more intuitive and user-friendly experience.Ensured compliance with updated accessibility standards, improving app usability for individuals with disabilities.

Chicago, Illinois, United States

Contracted AI/ML Engineer / Product Lead• Spearheaded the development of an AI/ML-powered DaaS API tailored for autonomous vehicles, achieving [95%] accuracy in object detection, addressing the problem of [reliable and accurate perception in complex environments] through [continuous model enhancement and iterative training on diverse datasets].• Orchestrated the integration of [TensorFlow, Core ML] frameworks, enabling real-time processing of [X] terabytes of sensor data per day, and [Y%] improvement in driverless safety, resolving the challenge of [autonomous mobility and ensuring safe operations] through [advanced analytics and real-time monitoring dashboards].• Collaborated with hardware specialists to refine sensor fusion methodologies, resulting in [X%] improvement in object detection accuracy and [Y%] reduction in false positives, addressing the problem of [reliable and robust perception] by [seamlessly integrating camera, LiDAR, and radar data streams].• Implemented advanced algorithms within the API, such as [reinforcement learning, path planning, etc.], achieving [X%] smoother maneuvers and [Y%] enhanced safety parameters, solving the challenge of [safe and efficient autonomous driving] through [intelligent decision-making and optimized trajectory planning].

Chicago, Illinois, United States

• Deployed an AI-powered gamification engine using reinforcement learning, increasing user engagement by 40% and improving driving behavior metrics by 25%, addressing the problem of [low engagement/unsafe driving habits] through gamification and personalized incentives.• Integrated computer vision techniques with YOLO, reducing distracted driving incidents by 40% and enhancing overall safety scores by 35% for teen and new drivers, resolving the issue of distracted driving and high-risk behavior by real-time video analysis and driver monitoring.• Developed and deployed machine learning models using TensorFlow, PyTorch, etc., achieving 97% accuracy in identifying high-risk driving situations, addressing the problem of potential accidents and safety concerns through predictive modeling and risk factor analysis.• Implemented NLP techniques to analyze user feedback, improving feature prioritization by [X%] and user satisfaction by [Y%], solving the challenge of [aligning product development with user needs] by [sentiment analysis and data-driven decision-making].Optimized data pipelines with [distributed computing frameworks], enabling real-time processing of [X] terabytes of driving data per day, addressing the problem of [scalability and performance bottlenecks] through [distributed computing and efficient data engineering].