Software Engineering Co-Op Spring 2027

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 bachelors or masters 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.

Additional Information :

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

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Equal Opportunity Employer including disability / veterans

By submitting an application for employment with Bosch you represent and warrant that: (a) the work product and materials you submit are your own and reflect your personal experience skills and qualifications; and (b) you have not used artificial intelligence or automated tools to generate alter or enhance application materials or responses in a manner that misrepresents your identity authorship experience capabilities or qualifications.

Remote Work :

No

Employment Type :

Full-time