Location: Ann Arbor, MI
Company: Torc Robotics
**About The Company** At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. **Meet the Team:** The mission of the Acceleration Team is to deploy trained Machine Learning Models on embedded hardware. This includes developing custom CUDA layers (usually guided by reference designs in Python) and implementing pre- and post-processing modules that convert raw data into model inputs and convert model outputs to usable signals. A major focus of the team is minimizing model inference latency by iteratively profiling and hand-tuning GPU kernels and C++ code. **What you'll do:** - Develop modern C++ and CUDA code for AI inference, including data processing algorithms and custom neural network layers - Optimize C++ and CUDA code guided by timing measurements and profiling to minimize processing latency - Utilize existing third-party and internal frameworks, libraries and tools - Work closely with other engineers and domain experts in a collaborative environment - Write functional and performance tests and documentation - Deliver high-quality, unit-tested, production code suitable for deployment in embedded, safety-critical environments **What you’ll need to succeed:** - Bachelor’s degree in Computer, Electrical, or Software engineering, or advanced degree - Deep understanding of memory management in C++, error handling, compilers and debuggers on Linux - Understanding of mechanisms of calling C/C++ functions from Python - Understanding of neural netw
This is a visa-sponsored position. Apply at avisajob.com/jobs/1775866708260