Motional is looking to evolve its on-board vehicle architecture for autonomous vehicles by improving the compute performance of current and next-generation systems through the development of a world-leading AI compute platform.
Requirements
- Experience with machine learning accelerators, including GPUs, NPUs, TPUs, and their programming environments, including CUDA, TensorRT, or similar technologies.
- Strong experience with modern C++ development in a Linux environment.
- Experience with parallel and high-performance computing.
- Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks.
- Experience with embedded systems development for ARM-based system-on-chip architectures.
- Experience working in a MLOps or DevOps environment.
Responsibilities
- Focus deeply on ML model deployment, integration of multiple ML models, and ML model optimization on embedded compute platforms.
- Dive deep into the full ML software stack. Analyze ML workload performance on a variety of hardware processors, optimize ML models, improve ML software, and help us continually improve our stack through the application of efficient and effective ML approaches.
- Design, develop, test, integrate, and optimize software and tools on a variety of ML compute architectures.
- Collaborate with deep learning experts in perception, prediction, and other autonomous driving application areas to enable algorithms on GPU, NPU, and other ML accelerator architectures.
- Optimize the utilization of GPU/NPU resources and sharing of GPU/NPU access across multiple programs running on the same system.
- Lead designs to determine the needs of the system and how to best meet those needs through continually improving our ML software stack.
- Advise peers and management on technical matters.
Other
- This role is hybrid from our Boston office. It requires two in-office days each week, ideally Tuesday and Thursday.
- A degree in Software Engineering, Computer Science, Electrical or Electronic Engineering, or similar technical field of study, or you have equivalent knowledge gained through your practical experience.
- Comfortable with experimentation and evaluating different options as we work towards finding solutions that work.
- Passion for self-driving technology and its potential for positive impact on the world.
- We celebrate diversity and are committed to creating an inclusive environment for all employees.
