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