BMW Customer Projects1. IPNext - Captain Atom Team (Jan 2024 - Present)Role: StdDiag Component Team MemberComponent Work: Contribute to the development and maintenance of the StdDiag component, an adaptive application built on ARA for collecting faults in the system, ..etc.Bug Resolution: Analyze and resolve bugs reported by team and customer testers.Feature Development: Implement new features and write integration tests to ensure quality.Client Engagement: Demonstrate completed work to clients, showcasing features and improvements.Daimler Customer Projects1. Media Framework AppAdapters Team (July 2023 – Jan 2024)Acted as an intermediate layer between UI and various entertainment audio sources, including online players (Tidal, Amazon Music), tuners, and offline players (Bluetooth and USB devices).- Analyzed and resolved bugs reported by team and customer testers.- Added unit and component tests to enhance software reliability.- Created detailed documentation for different architectural components.Key Achievements:- Enhanced testing coverage and documentation, contributing to higher software quality and maintainability.2. Online Player Team (March 2023 – July 2023)- Managed the online music experience for Mercedes-Benz cars, supporting providers like Spotify, Apple Music, and Tidal.- Analyzed and resolved bugs reported by team and customer testers.- Improved logging mechanisms, leading to the recovery of numerous discarded messages from traces.Key Achievements:- Optimized logging processes, contributing to more effective debugging and issue resolution.3. Browser Team (July 2022 – March 2023)- Contributed to the development of the browser app for Mercedes-Benz cars targeting the Chinese market.- Analyzed and resolved bugs reported by team and customer testers.- Managed the integration process for the browser app.Key Achievements:- Achieved a 5x improvement in the browser app build time, significantly enhancing development efficiency..

- Implemented machine learning pipelines in C++ as provided by researchers to integrate into the SDK.- Utilized CMake to build libraries and link with various third-party frameworks like TensorFlow, PyTorch, and Kaldi.- Developed SWIG interfaces to create wrappers for multiple target languages, including Python, Java, and C#.- Created GitLab CI jobs for building, testing, and deploying the SDK on both Linux and Windows platforms.Key Achievements:- Contributed to the development of IDefy, enhancing the SDK with advanced machine learning capabilities.- Successfully integrated complex machine learning pipelines into the SDK, ensuring seamless functionality across different platforms.- Improved the efficiency and reliability of the build and deployment process through effective CI/CD practices.Skills Gained:- Proficiency in C++ and CMake for library development and third-party integration.- Experience with SWIG for multi-language wrapper development.- Strong understanding of CI/CD pipelines using GitLab CI.- Enhanced skills in software documentation, unit testing, and cross-platform development.

- Collected and processed video snapshots to identify pick-up and drop actions in retail environments.- Applied the OpenPose model for pose estimation, feeding results into an action recognition model.- Utilized a pre-trained ST-GCN action recognition model on customer datasets through transfer learning.- Developed APIs to integrate Mechanical Turks into Parl.AI, enhancing the Fluido App using Flask.Key Achievements:- Designed and implemented a robust system for recognizing shopping actions (pick-up and drop) in supermarkets.- Successfully applied advanced machine learning models and transfer learning techniques to improve action recognition accuracy.- Streamlined data collection and processing workflows to support efficient model training and evaluation.Skills Gained:- Advanced knowledge of machine learning and action recognition techniques.- Hands-on experience with OpenPose and ST-GCN models.- Proficiency in developing APIs and integrating AI solutions using Flask.- Strong background in Python programming and using libraries such as TensorFlow, PyTorch, and NumPy.

- Developed an internal knowledge base system chatbot for Attijariwafa Bank, enhancing employee information retrieval.- Utilized the Rasa framework to create and integrate the chatbot into customer web applications.Key Achievements:- Successfully streamlined the process for employees to access information, improving overall efficiency.- Integrated advanced natural language processing capabilities to enhance user interactions.Skills Gained:- Expertise in chatbot development using Rasa.- Proficiency in Python and Flask for backend development.- Experience in integrating AI solutions into existing web applications.