The mission of the Application Engine Team is to provide a robust, efficient, and flexible platform for integrating and managing various deep learning models and processes in the context of L4 autonomous trucking. It aims to streamline development workflows, enhance team efficiency, and ensure consistent performance and safety standards.
Requirements
- Proficiency in C++ (C++14 or newer) and Linux development.
- Hands-on experience with CUDA
- Understanding of parallel programming, GPU acceleration, or real-time systems.
- Familiarity with PCIe, Ethernet-based interconnects, or embedded device programming.
- Familiarity with and at least one ML framework (e.g., PyTorch).
Responsibilities
- Implement and optimize software components supporting distributed execution of ML models on embedded GPU platforms.
- Contribute to message-passing, resource management, and runtime feature development for the App Engine SDK.
- Profile and optimize GPU utilization, reducing latency and maximizing throughput for ML workloads.
- Collaborate with feature teams to integrate and validate App Engine functionality in vehicle and simulation environments.
- Maintain clean, efficient C++ code and unit/integration tests.
Other
- Bachelor’s degree in Computer Science, Electrical Engineering, or related field with 4+years of experience, OR Master’s with 2+ years, OR PhD with 1+ years.
- Strong problem-solving skills and ability to collaborate in a fast-paced environment.
