Embedded AI & Vision Co-op — Real-Time Systems

Bosch USA; Fountain Inn (SC); On-site; USD 32,000 - 45,000; Full time

Job summary

Bosch Rexroth seeks an Embedded AI Software Engineering Intern/Co-op for the summer to work on cutting-edge embedded AI and CV apps for mobile machines. You will optimize AI models and real-time pipelines on resource-constrained hardware, and collaborate with the software team to improve inference performance and hardware utilization.

You will gain hands-on experience developing, deploying, profiling, and optimizing AI-powered vision systems on embedded platforms, with exposure to hardware

Qualifications

• Currently pursuing a bachelor’s or master’s degree in a relevant technical field.
• Familiarity with C/C++ programming.
• Fundamental understanding of embedded systems and software development.
• Basic knowledge of AI, ML, or CV concepts.
• Familiarity with Linux development environments.

Responsibilities

• Collaborate to develop and optimize embedded AI and computer vision applications for mobile machines.
• Deploy, benchmark, and optimize AI models on embedded targets, including hardware accelerators.
• Optimize real-time video processing and AI inference pipelines to improve throughput and reduce latency.
• Profile and troubleshoot on-target performance bottlenecks in acquisition, preprocessing, inference, and output.
• Explore AI model optimization techniques such as quantization and pruning.

Skills

C/C++ programming

Embedded systems

Linux development

Analytical thinking

Team collaboration

Problem solving

Education

Bachelor’s or Master’s degree in Computer Engineering / Computer Science / Electrical Engineering

Tools

PyTorch

TensorFlow

ONNX

OpenCV

Job description

Bosch Rexroth seeks an Embedded AI Software Engineering Intern/Co-op for the summer to work on cutting-edge embedded AI and CV apps for mobile machines. You will optimize AI models and real-time pipelines on resource-constrained hardware, and collaborate with the software team to improve inference performance and hardware utilization.

You will gain hands-on experience developing, deploying, profiling, and optimizing AI-powered vision systems on embedded platforms, with exposure to hardware