Edge Perception Model Algorithm Engineer Intern
Algorithms · Internship · Shenzhen (work arrangement discussed for the role)
RMB 200–400 / day
Role overview
Support training, evaluation, edge deployment, and performance optimization of perception models.
Responsibilities
- Assist with training, evaluation, and tuning of edge-perception models.
- Validate facial detection and affect-recognition functions through data analysis and metric evaluation.
- Perform foundational inference-speed and resource-use optimization and performance testing.
- Assist with model integration, edge deployment, and issue diagnosis.
Requirements
- Currently enrolled in an undergraduate or graduate program in computer science, electronic engineering, automation, or a related field.
- Foundational computer-vision knowledge in at least one area such as object detection, image classification, or keypoint detection.
- Familiarity with PyTorch or TensorFlow and model training and tuning.
- Good experimental-record and problem-analysis skills to complete validation and iteration under guidance.
- Available for at least three months and at least four days per week on site.
Preferred qualifications
- Awareness of ONNX, TensorRT, mobile deployment, or edge optimization.
- Coursework, lab, competition, or open-source contributions with work samples or code links.
- Practical experience with affective computing, facial detection, or multimodal perception.
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