ML Engineer, II - App Engine

<p><strong><span data-contrast="auto">About the Company</span></strong><span data-ccp-props="{}">&nbsp;</span></p> <p><span data-contrast="auto">At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.</span>&nbsp;<br><span data-contrast="auto">A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. </span><a href="https://torc.ai/daimler-testing-automated-trucks-public/"><span data-contrast="none"><span data-ccp-charstyle="Hyperlink">Now a part of the Daimler family</span></span></a><span data-contrast="auto">, we are focused solely on developing software for automated trucks to transform how the world moves freight.</span>&nbsp;<br><span data-contrast="auto">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.</span><span data-ccp-props="{}">&nbsp;</span></p> <p><strong><span data-contrast="none">Meet the Team</span></strong></p> <p>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.</p> <p><strong><span data-contrast="none">What&nbsp;You’ll&nbsp;Do</span></strong><span data-ccp-props="{}">&nbsp;</span></p> <ul> <li>Development of a processing pipeline SDK capable of spanning multiple distributed System on a Chips using Ethernet, PCIe, and similar to move data through different processing stages.</li> <li>Optimization of concurrent usage of resources (Memory, GPU) for parallel execution of trained models on a single System on a Chip</li> <li>Development of a runtime environment, which uses the App Engine SDK to deploy machine learning based virtual driver applications.</li> <li>SDK Feature development to support the creation of Virtual Driver Software</li> <li>Support Virtual Driver Division with their usage of the Application Engine</li> <li>Creation of high-quality code including test cas