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# ML Engineer, II - App Engine

- **Company:** Torc Robotics, Inc.
- **Location:** Ann Arbor, MI, United States
- **Experience:** Expert
- **Salary:** $153,200.0 - $183,800.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Google App Engines, C++ (Programming Language), Nvidia CUDA, Computer Engineering, Linux, Distributed Systems, Embedded Software, Ethernet, Machine Learning, PCI Express, Software Engineering, System on a Chip, Test Case, Graphics Processing Unit (GPU), Pytorch, Deep Learning, Application Engine, Information Technology, TensorRT
- **Published:** June 24, 2026
- **Apply:** https://www.dice.com/job-detail/c70f8ec5-fbb5-4330-9a5e-fb418044521a

## About the Role

* Bachelor's degree in Computer Engineering, Electrical Engineering, or Software Engineering, Computer Science or advanced degree with 5+ years experience
 * Experience with Embedded Software Development, especially with a focus on GPUs
 * Experience with TensorRT and CUDA
 * Experience in the development of real-time distributed systems
 * Profound knowledge of C++
 * Familiarity with machine learning technologies (e.g. PyTorch)
 * Experience with Linux

Bonus Points

 * Experience developing SDK's for complex embedded systems, especially those featuring GPUs or multiple SOCs.
 * Experience in autonomous robotic or vehicle systems.
 * Knowledge of computer architecture principles such as pipelining, memory hierarchy, locality, etc.

## Description

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 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

 * 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.
 * Optimization of concurrent usage of resources (Memory, GPU) for parallel execution of trained models on a single System on a Chip
 * Development of a runtime environment, which uses the App Engine SDK to deploy machine learning based virtual driver applications.
 * SDK Feature development to support the creation of Virtual Driver Software
 * Support Virtual Driver Division with their usage of the Application Engine
 * Creation of high-quality code including test case development


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