👋 About the Team
The NetsPresso Core Research Team drives the expansion and improvement of the core technologies behind NetsPresso’s modular AI platform. We research and develop HW-aware AI models through the Trainer, design novel compression techniques via the Compressor, and enable support for new edge devices using the Converter.
📌 What You’ll Do at This Position
Work on optimizing and deploying diverse AI models for on-device use. You’ll use NetsPresso to compress and optimize models, analyze performance, and contribute to improvements. You’ll also transform models for real device deployment, validate performance through real-time inference tests, and help maximize both efficiency and quality.
✅ Key Responsibilities
- Support optimization and deployment of on-device AI models
- Assist with lightweighting methods such as Pruning, Quantization, Knowledge Distillation
- Support model conversion and optimization using TensorRT, TensorFlow Lite, ONNX, etc.
- Assist with optimization of a variety of AI models
- Generative AI (large language model, stable diffusion model, etc.)
- Computer Vision (classification, object detection, segmentation, etc.) and more
- Contribute to performance analysis and improvements of AI models
✅ Requirements
- Currently pursuing or holding a degree in Computer Engineering, Electrical Engineering, or related fields
- Proficient in Python with relevant project experience
- Experience with at least one deep learning framework (e.g., PyTorch, TensorFlow)
- Strong interest in developing deep learning and machine learning models
- Understanding of basic algorithms and data structures
- Eligible for overseas travel
✅ Pluses
- Understanding or hands-on experience with model compression (Pruning, Quantization, Knowledge Distillation)
- Familiarity with libraries such as TensorRT, TensorFlow Lite, ONNX, ArmNN
- Experience developing or optimizing generative AI models (LLM, LVM, Text-to-Image, etc.)
- Experience deploying deep learning models on embedded devices
- Participation in AI-related projects or academic research
✅ Hiring Process
- Document Screening →Assignment → 1st Interview
🤓 A Message from the Team
As an AI Engineer Intern, you’ll join colleagues who are deeply curious about AI technologies and committed to advancing domain knowledge. We’re looking for someone who can adapt quickly in a fast-paced environment, proactively suggest improvements, and take ownership of their work.
At Core Research, developers and researchers collaborate closely—communication is at the heart of how we work. We value a be proactive attitude, a willingness to dive deep into new areas, and a mindset of continuous growth alongside your teammates.
Please Check Before Applying! 👀
- This job posting is open continuously, and it may close early upon completion of the hiring process.
- Resumes that include sensitive personal information, such as salary details, may be excluded from the review process.
- Providing false information in the submitted materials may result in the cancellation of the application.
- Please be aware that references will be checked before finalizing the hiring decision.
- Compensation will be discussed separately upon successful completion of the final interview.
- There will be a probationary period after joining, and there will be no discrimination in the treatment during this period.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
🔎 Helpful materials
👋 About the Team
The NetsPresso Core Research Team drives the expansion and improvement of the core technologies behind NetsPresso’s modular AI platform. We research and develop HW-aware AI models through the Trainer, design novel compression techniques via the Compressor, and enable support for new edge devices using the Converter.
📌 What You’ll Do at This Position
Work on optimizing and deploying diverse AI models for on-device use. You’ll use NetsPresso to compress and optimize models, analyze performance, and contribute to improvements. You’ll also transform models for real device deployment, validate performance through real-time inference tests, and help maximize both efficiency and quality.
✅ Key Responsibilities
- Support optimization and deployment of on-device AI models
- Assist with lightweighting methods such as Pruning, Quantization, Knowledge Distillation
- Support model conversion and optimization using TensorRT, TensorFlow Lite, ONNX, etc.
- Assist with optimization of a variety of AI models
- Generative AI (large language model, stable diffusion model, etc.)
- Computer Vision (classification, object detection, segmentation, etc.) and more
- Contribute to performance analysis and improvements of AI models
✅ Requirements
- Currently pursuing or holding a degree in Computer Engineering, Electrical Engineering, or related fields
- Proficient in Python with relevant project experience
- Experience with at least one deep learning framework (e.g., PyTorch, TensorFlow)
- Strong interest in developing deep learning and machine learning models
- Understanding of basic algorithms and data structures
- Eligible for overseas travel
✅ Pluses
- Understanding or hands-on experience with model compression (Pruning, Quantization, Knowledge Distillation)
- Familiarity with libraries such as TensorRT, TensorFlow Lite, ONNX, ArmNN
- Experience developing or optimizing generative AI models (LLM, LVM, Text-to-Image, etc.)
- Experience deploying deep learning models on embedded devices
- Participation in AI-related projects or academic research
✅ Hiring Process
- Document Screening →Assignment → 1st Interview
🤓 A Message from the Team
As an AI Engineer Intern, you’ll join colleagues who are deeply curious about AI technologies and committed to advancing domain knowledge. We’re looking for someone who can adapt quickly in a fast-paced environment, proactively suggest improvements, and take ownership of their work.
At Core Research, developers and researchers collaborate closely—communication is at the heart of how we work. We value a be proactive attitude, a willingness to dive deep into new areas, and a mindset of continuous growth alongside your teammates.
Please Check Before Applying! 👀
- This job posting is open continuously, and it may close early upon completion of the hiring process.
- Resumes that include sensitive personal information, such as salary details, may be excluded from the review process.
- Providing false information in the submitted materials may result in the cancellation of the application.
- Please be aware that references will be checked before finalizing the hiring decision.
- Compensation will be discussed separately upon successful completion of the final interview.
- There will be a probationary period after joining, and there will be no discrimination in the treatment during this period.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
🔎 Helpful materials