TORC Robotics
Machine Learning Engineer I - App Engine (CUDA)
TORC Robotics, Ann Arbor, Michigan, us, 48113
Machine Learning Engineer I - App Engine (CUDA)
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. The Application Engine focuses on facilitating the creation of scalable, reproducible, and safety-compliant components, enabling feature teams to efficiently develop and deploy advanced autonomous driving features. What You'll Do 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. What You'll Need To Succeed Bachelor's degree in Computer Science, Electrical Engineering, or related field with 04 years of experience, OR Master's with 02 years, OR PhD with 02 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. Bonus Points Internship or project experience involving distributed systems, GPU programming, or embedded software. Perks Of Being A Full-time Torc'r A competitive compensation package that includes a bonus component and stock options 100% paid medical, dental, and vision premiums for full-time employees 401K plan with a 6% employer match Flexibility in schedule and generous paid vacation (available immediately after start date) Company-wide holiday office closures AD+D and Life Insurance Hiring Range For Job Opening US Pay Range $132,400 - $158,900 USD
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. The Application Engine focuses on facilitating the creation of scalable, reproducible, and safety-compliant components, enabling feature teams to efficiently develop and deploy advanced autonomous driving features. What You'll Do 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. What You'll Need To Succeed Bachelor's degree in Computer Science, Electrical Engineering, or related field with 04 years of experience, OR Master's with 02 years, OR PhD with 02 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. Bonus Points Internship or project experience involving distributed systems, GPU programming, or embedded software. Perks Of Being A Full-time Torc'r A competitive compensation package that includes a bonus component and stock options 100% paid medical, dental, and vision premiums for full-time employees 401K plan with a 6% employer match Flexibility in schedule and generous paid vacation (available immediately after start date) Company-wide holiday office closures AD+D and Life Insurance Hiring Range For Job Opening US Pay Range $132,400 - $158,900 USD