👋 About the Team
The NetsPresso Platform Team at Nota AI designs and implements core platforms and software that transform AI model lightweighting and optimization research into real-world products.
Our organization consists of Model Representation, Quantization, Graph Optimization, Model Engineering, and SW Engineering units. Specifically, the Model Representation Part unifies models from various deep learning frameworks into our proprietary NPIR (NetsPresso Intermediate Representation). This foundational step enables the application of key optimization technologies such as quantization, graph optimization, and compression.
By integrating diverse framework models into a single NPIR, we achieve technical versatility, scale support for the latest AI models and hardware, and maximize inference efficiency by optimizing the logical structure of deep learning models for target runtime environments.
📌 What You’ll Do at This Position
In this position, you will tackle real-world challenges across various industrial domains using AI technology. You will participate in the entire lifecycle of evolving a model into a field-ready AI solution. Through technical deep-dives based on the latest research papers and performance analysis, you will gain a balanced experience between AI research and practical development. You will also collaborate with experienced AI application developers to build production-grade AI systems.
✅ Key Responsibilities
IR Implementation & Maintenance
- NPIR Graph Structure Development: Implement and extend the data structures of NetsPresso Intermediate Representation (NPIR) to represent diverse model architectures from various deep learning frameworks.
- Framework Conversion Logic Development: Develop and validate conversion logic to bridge multiple frameworks (such as PyTorch and ONNX) with NPIR.
Expanding Support for Latest AI Models & Diverse Hardware
- Support for Broad Model Domains: Research and develop conversion and optimization technologies for not only Computer Vision but also the latest Generative AI models such as LLMs, VLMs, and Diffusion models.
- Ensuring Universal Compatibility: Develop compatibility technologies to ensure optimal performance across various hardware environments, from Edge Devices (including NPUs) to Data Center GPUs.
✅ Requirements
- Degree in Computer Science, Electronic Engineering, or a related field.
- Proficiency in Python with the ability to write Object-Oriented Programming (OOP) and clean code.
- Minimum of 3 years of relevant professional experience.
- Experience with deep learning graphs and graph-related algorithms.
- Experience in PyTorch-based deep learning model optimization.
- No disqualifications for overseas travel.
✅ Pluses
- Experience in compiler/IR-related projects such as ONNX, MLIR, or LLVM.
- Hands-on experience applying graph optimization and lightweighting techniques.
- Experience in model optimization using libraries such as ExecuTorch, ONNX, TensorRT, or AIMET.
- Experience publishing papers related to deep learning model optimization and lightweighting.
✅ Hiring Process
- Document Screening →Pre-assignment Presentation → 1st Interview → 2nd Interview → 3rd Interview
(Additional assignments may be included during the process.)
🤓 A Message from the Team
You will be part of productizing the unified IR that serves as the foundation of NetsPresso. You will contribute to designing and developing our unique NPIR while analyzing the characteristics of various frameworks and hardware. In this role, you will see how on-device AI lightweighting and optimization techniques are applied to actual products and solve technical hurdles to ensure latest models run efficiently. As an AI Engineer, you will find great satisfaction in implementing theoretical research into a real-world software stack.
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.
- To support the employment of persons with disabilities, you may optionally submit a copy of your disability registration certificate under “Additional Documents,” if administrative verification is required. Submission is optional and does not affect the evaluation process.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
🔎 Helpful materials
👋 About the Team
The NetsPresso Platform Team at Nota AI designs and implements core platforms and software that transform AI model lightweighting and optimization research into real-world products.
Our organization consists of Model Representation, Quantization, Graph Optimization, Model Engineering, and SW Engineering units. Specifically, the Model Representation Part unifies models from various deep learning frameworks into our proprietary NPIR (NetsPresso Intermediate Representation). This foundational step enables the application of key optimization technologies such as quantization, graph optimization, and compression.
By integrating diverse framework models into a single NPIR, we achieve technical versatility, scale support for the latest AI models and hardware, and maximize inference efficiency by optimizing the logical structure of deep learning models for target runtime environments.
📌 What You’ll Do at This Position
In this position, you will tackle real-world challenges across various industrial domains using AI technology. You will participate in the entire lifecycle of evolving a model into a field-ready AI solution. Through technical deep-dives based on the latest research papers and performance analysis, you will gain a balanced experience between AI research and practical development. You will also collaborate with experienced AI application developers to build production-grade AI systems.
✅ Key Responsibilities
IR Implementation & Maintenance
- NPIR Graph Structure Development: Implement and extend the data structures of NetsPresso Intermediate Representation (NPIR) to represent diverse model architectures from various deep learning frameworks.
- Framework Conversion Logic Development: Develop and validate conversion logic to bridge multiple frameworks (such as PyTorch and ONNX) with NPIR.
Expanding Support for Latest AI Models & Diverse Hardware
- Support for Broad Model Domains: Research and develop conversion and optimization technologies for not only Computer Vision but also the latest Generative AI models such as LLMs, VLMs, and Diffusion models.
- Ensuring Universal Compatibility: Develop compatibility technologies to ensure optimal performance across various hardware environments, from Edge Devices (including NPUs) to Data Center GPUs.
✅ Requirements
- Degree in Computer Science, Electronic Engineering, or a related field.
- Proficiency in Python with the ability to write Object-Oriented Programming (OOP) and clean code.
- Minimum of 3 years of relevant professional experience.
- Experience with deep learning graphs and graph-related algorithms.
- Experience in PyTorch-based deep learning model optimization.
- No disqualifications for overseas travel.
✅ Pluses
- Experience in compiler/IR-related projects such as ONNX, MLIR, or LLVM.
- Hands-on experience applying graph optimization and lightweighting techniques.
- Experience in model optimization using libraries such as ExecuTorch, ONNX, TensorRT, or AIMET.
- Experience publishing papers related to deep learning model optimization and lightweighting.
✅ Hiring Process
- Document Screening →Pre-assignment Presentation → 1st Interview → 2nd Interview → 3rd Interview
(Additional assignments may be included during the process.)
🤓 A Message from the Team
You will be part of productizing the unified IR that serves as the foundation of NetsPresso. You will contribute to designing and developing our unique NPIR while analyzing the characteristics of various frameworks and hardware. In this role, you will see how on-device AI lightweighting and optimization techniques are applied to actual products and solve technical hurdles to ensure latest models run efficiently. As an AI Engineer, you will find great satisfaction in implementing theoretical research into a real-world software stack.
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.
- To support the employment of persons with disabilities, you may optionally submit a copy of your disability registration certificate under “Additional Documents,” if administrative verification is required. Submission is optional and does not affect the evaluation process.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.