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- ÀÓº£µðµå Çϵå¿þ¾î¿¡ Computer Vision Deep Learning ¸ðµ¨ ±¸µ¿
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1. ÇÐÀ§: °ü·Ã ºÐ¾ß Çлç ÀÌ»ó
- AI, Computer Science, Software Engineering, Electrical and Electronics Engineering, ȤÀº À¯»ç Çаú
2. °æ·Â: °ü·Ã ºÐ¾ß 5³â ÀÌ»ó ȤÀº °æ·Â ±×¿¡ ÁØÇÏ´Â °æ·Â
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- S/W °³¹ß ¹× »óÇ°È °æÇè
- ÀÓº£µðµå ȯ°æ ±â¹Ý SW ¼³°è ¹× °³¹ß °æÇè
- µ¿·á¿Í ¿øÈ°ÇÑ ÀÇ»ç¼ÒÅë ´É·Â ¹× ¸®´õ½Ê
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- ÆÀÀÇ ¸®´õ·Î¼ ÇÁ·ÎÁ§Æ®¸¦ ¼º°øÀûÀ¸·Î À̲ö °æÇè
- RTOS, ÀÓº£µðµå Æß¿þ¾î/µå¶óÀ̹ö °³¹ß °æÇè
- Ä«¸Þ¶ó(¼¾¼, ±¤Çаè, ISP µî)¿¡ ´ëÇÑ ±íÀº ÀÌÇØ
- DevOps / MLOps ÆÄÀÌÇÁ¶óÀÎ ¼³°è ¹× ±¸Çö °æÇè
- ÄÄÇ»ÅÍ Çϵå¿þ¾î¿¡ ´ëÇÑ ±íÀº ÀÌÇØ(¼¹ö, ½ºÅ丮Áö, ³×Æ®¿öÅ©, SoC µî)
- ¸ðºô¸®Æ¼ ºÐ¾ß¿¡¼ »ç¿ëÇÏ´Â AP(Ambarella, Ti, Qualcomm, Exynos, etc.)¸¦ ÀÌ¿ëÇÑ AI ±â¹Ý SW ¼³°è ¹× °³¹ß °æÇè
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🔎Team Information
The Research & Development Division develops in-cabin monitoring systems and Occupant monitoring systems to enhance the safety of drivers and passengers. Our goal is to ship faster and more reliable ML-based applications to the vehicles to come.
💻Responsibilities
- Running Computer Vision Deep Learning models on embedded hardware
- Quantitative evaluation and analysis of deep learning models in real vehicle environments
- Improving the performance of embedded applications
- Responding to quality assurance and certification processes required for mass production of other ICMS products
✔️Qualifications
1. Education: Bachelor's degree or higher in a related field
- AI, Computer Science, Software Engineering, Electrical and Electronics Engineering, or other similar disciplines
2. Experience (Industry experience): Bachelor¡¯s degree + 5 years or Master¡¯s degree
3. Required Skills:
- Experience in computer vision & deep learning development
- Ability to design deep learning networks from scratch
- Experience in S/W development and commercialization
- Experience in designing and developing embedded environment-based SW
- Ability to communicate smoothly with colleagues and leadership
- Ability to communicate in English with foreign engineers
✨Preferred Qualifications
- More than 5 years of development experience in the mobility field
- Experience in successfully leading a project as a team leader
- Experience in developing RTOS, embedded firmware/driver
- Deep understanding of cameras (sensors, optical systems, ISPs, etc.)
- Experience in designing and implementing DevOps/MLOps pipelines
- Deep understanding of computer hardware (servers, storage, networks, SoCs, etc.)
- Experience in designing and developing AI-based SW using APs (Ambarella, Ti, Qualcomm, Exynos, etc.) used in the mobility field