Machine Learning Engineer I - App Engine (CUDA)

Torc Robotics is focused on providing a robust platform for integrating deep learning models in the context of L4 autonomous trucking. They are seeking a Machine Learning Engineer I to develop and maintain components of the App Engine runtime, assist in data handling between compute nodes, and collaborate with senior engineers to enhance their skills in GPU programming and embedded ML deployment. Responsibilities: - Develop and maintain components of the App Engine runtime and SDK supporting ML workloads on embedded GPUs. - Assist in implementing message-passing and data handling between distributed compute nodes. - Contribute to testing, debugging, and performance tuning of ML integration features. - Work closely with senior engineers to learn and apply best practices in GPU programming and embedded ML deployment. Qualification: - Bachelor's degree in Computer Science, Electrical Engineering, or related field with 0–4 years of experience, OR Master's with 0–2 years, OR PhD with 0–2 years. - Strong programming skills in C++ and familiarity with Linux development environments. - Exposure to CUDA, GPU programming concepts, or machine learning frameworks (e.g., PyTorch). - Eagerness to learn, contribute, and grow in an applied ML engineering environment. Preferred: - Internship or project experience involving distributed systems, GPU programming, or embedded software.

Torc Robotics provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense markets through strategic partnerships.