• Develop new approaches and implement improvements to existing algorithms for sensor calibration for ADAS using both classical and deep learning methods. • Work with large amounts of real and synthetic data to evaluate and improve the algorithmic and computational performance of sensor calibration. • Develop and optimize software architecture and frameworks for real-world performance towards internal and external customer requirements. • Work with a variety of sensor modalities: camera, LIDAR, radar, IMU, GPS, odometry, etc. • Develop unit tests, documentation for features, evaluate quality and propose improvements and corrective actions. • Develop highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA). • Develop production code to strict quality and safety standards such as MISRA and AUTOSAR. • Develop and maintain fleet monitoring tools supporting calibration of a large vehicle fleet. • Perform in-vehicle tests and troubleshooting, mining/analyzing data and completing drive missions. • Adopt and improve calibration algorithms on existing and new vehicle variants.

• Design, implement and maintain system software that enables communication between GPUs • Participate in the architectural definition and design of next-generation communication hardware and software to support large scale computing platforms • Work with cross-disciplinary teams to understand business requirements and align software direction to meet those needs

• Define and drive the mobile platform vision – Establish a culture of technical excellence, innovation, and collaboration. • Lead and grow a high-performing team – Recruit, mentor, and develop engineering leaders and individual contributors, fostering a sense of ownership and accountability. • Deliver a world-class mobile experience – Lead the development of a robust, native iOS application that enables users to apply for loans, manage their accounts, and handle repayments seamlessly. • Operationalize success metrics – Establish clear KPIs to measure engineering efficiency, product performance, and business impact. • Drive automation and process improvements – Champion best practices in mobile development, CI/CD, testing, and deployment. • Strategic Roadmapping & Prioritization – Partner with cross-functional teams to develop and execute medium- and long-term mobile strategies.

• Deliver a project that helps generalize model configuration, enables no-code model deploys, or improves integration testing across ML systems. • Own the design and implementation of significant scalability improvements and additions to the ML platform.