Additionalinformation

Additional Information

Indefinite U.S. work authorized individuals only. Future sponsorship for work authorization unavailable.

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Companydescription

Company Description

Our drive and control technologies ensure efficient, powerful, and safe movement in machines and systems of any size. We inspire our customers with intelligent components, tailored system solutions, and services – from fully connected applications to the factory of the future. Bosch Rexroth is dedicated to making the world a better place through innovation and technology. We are looking for associates who will take on our customers’ challenges with passion and persistence until the right solution is found and who will thrive in a face-paced, collaborative, and exciting environment.

Jobdescription

Job Description

We are seeking a motivated and talented Embedded AI Software Engineering Intern/Co-op to join our team for the summer. As an intern, you will work on cutting-edge embedded AI and computer vision applications for mobile machines, with a focus on optimizing AI models and real-time processing pipelines for deployment on embedded hardware.

This role provides hands-on experience developing, deploying, profiling, and optimizing AI-powered vision systems on resource-constrained embedded platforms. You will work closely with our software engineering team to improve inference performance, reduce processing latency, and maximize hardware utilization while maintaining real-time system performance.

Responsibilities

• Collaborate with the software development team to develop and optimize embedded AI and computer vision applications for mobile machines.
• Deploy, benchmark, and optimize AI models for execution on embedded targets, including platforms equipped with hardware AI accelerators.
• Optimize real-time video processing and AI inference pipelines to improve throughput, reduce latency, and minimize CPU, GPU, and memory utilization.
• Profile and troubleshoot on-target performance bottlenecks involving image acquisition, preprocessing, inference, postprocessing, and video output.
• Explore AI model optimization techniques such as quantization, pruning, and hardware-specific acceleration to improve inference efficiency.
• Develop and optimize software components in C/C++ for embedded Linux and real-time operating systems.
• Integrate AI models with camera systems, sensor inputs, and embedded communication interfaces.
• Develop testing and benchmarking tools to evaluate model accuracy, execution time, memory consumption, and end-to-end pipeline performance.
• Document software architecture, optimization strategies, performance results, and implementation details.
• Participate in team meetings, code reviews, and technical discussions.

Qualifications

Minimum Qualifications

• Currently pursuing a bachelor's or master's degree in Computer Engineering, Computer Science, Electrical Engineering, or another relevant technical field.
• Familiarity with C/C++ programming.
• Fundamental understanding of embedded systems and software development.
• Basic knowledge of artificial intelligence, machine learning, or computer vision concepts.
• Familiarity with Linux development environments.
• Strong analytical, debugging, and problem-solving skills.
• Excellent communication and collaboration abilities.

Preferred Qualifications

• Experience deploying AI or computer vision models on embedded hardware.
• Familiarity with AI frameworks and deployment tools such as PyTorch, TensorFlow, TensorFlow Lite, or ONNX.
• Experience optimizing neural networks through quantization, model compression, or hardware-specific inference acceleration.
• Familiarity with embedded AI accelerators, GPUs, or NPUs, including platforms such as Texas Instruments TDA4.
• Experience with real-time video processing frameworks such as GStreamer, OpenCV, or similar technologies.
• Experience with embedded Linux, QNX, or other real-time operating systems.
• Familiarity with performance profiling tools and optimization techniques for CPU, GPU, memory, and system-level bottlenecks.
• Knowledge of image processing, object detection, or semantic segmentation models.
• Experience with embedded communication protocols such as CAN or Ethernet.
• Familiarity with cross-compilation, hardware debugging, and on-target software development.