Á¦¸ñ | [Expert] AI¼¾ÅÍ AI Product Data Engineer (AI¼¾ÅÍ) | Á¶È¸¼ö | 292 |
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ä¿ë±â°ü | SKÅÚ·¹ÄÞ | ÇÐÀ§±¸ºÐ | ¼®¡¤¹Ú»ç |
ºÐ¾ß | AI | ¸ðÁý±â°£(¸¶°¨ÀÏ) | 2019.10.06 |
÷ºÎÆÄÀÏ | µî·ÏÀÏ | 2019.09.11 | |
* SKÅÚ·¹ÄÞ AI¼¾ÅÍÀÇ Data Machine Intelligence GroupÀº SKT ³»/¿ÜºÎ µ¥ÀÌÅ͸¦ ¹ÙÅÁÀ¸·Î AI°ü·Ã ¼ºñ½º¸¦ °³¹ßÇÏ°í ÀÖÀ¸¸ç AI Product Engineering ÆÀÀº µ¥ÀÌÅ͸¦ È¿°úÀûÀ¸·Î ºÐ¼®ÇÏ°í ´Ù¾çÇÑ AI±â¹Ý ¼ºñ½º¿¡ ¿¬°áÇÒ ¼ö ÀÖ´Â Big Data/AI Platform °³¹ßÇÏ°í ÀÖ½À´Ï´Ù. -¸ðµç ÆÀ¿øÀÌ Á÷Á¢ Äڵ带 Â¥°í ÄÚµå·Î Ä¿¹Â´ÏÄÉÀ̼ÇÀ» ÇÏ¸ç ¾Æ·¡´Â AI Product Engineering ÆÀ¿¡¼ »ç¿ëÇÏ´Â ±â¼ú°ú ÀÎÇÁ¶ó ȯ°æÀÔ´Ï´Ù. ◾Hive as data warehouse, Spark for distributed processing, Kafka as a messaging system. ◾S3, Dynamo db, Azure Blob, Google Cloud Storage to expose data. ◾Sbt for compilation and dependency management. ◾RDS for access to relational databases, HDFS, S3 as a distributed storage system. ◾YARN and Kubernetes as cluster orchestration system. ◾Airflow as a process manager, Gitlab-CI as a continuous integration manager. ◾Baremetal, AWS, Azure, GCP as infra. 1. ÁÖ¿ä ¼öÇà ¾÷¹« ¹× ¿ªÇÒ ◾¹èÄ¡¿Í ½ºÆ®¸² µ¥ÀÌÅÍ ÆÄÀÌÇÁ ¶óÀÎ °³¹ß ¹× ¿î¿µ ◾µ¥ÀÌÅÍ ºÐ¼®°¡ ¹× ÇÁ·Î´öÆ® ¸Å´ÏÀú¿ÍÀÇ Çù¾÷ ◾¹Ýº¹ÀûÀÎ ¾÷¹«ÀÇ ÀÚµ¿È 2. ÇÊ¿ä ¿ª·® ◾Æ®·¯ºí ½´ÆÃ, µð¹ö±ë, ÀÚµ¿È¿¡ ´ëÇÑ ¿Á¤ ◾ÆÛÆ÷¸Õ½º Æ©´×¿¡ ´ëÇÑ ¿Á¤ ◾½Ç½Ã°£ ºÐ»ê ó¸® ½Ã½ºÅÛ °³¹ß ¹× ¿î¿µ °æÇè ◾µÎ °¡Áö ÀÌ»óÀÇ ÇÁ·Î±×·¡¹Ö ¾ð¾î¿Í Æз¯´ÙÀÓ¿¡ °üÇÑ Àü¹®¼º ◾»ó¿ë ¼ºñ½º ¹× ¼Ö·ç¼Ç °³¹ß ¹× ¿î¿µ °æÇè 3. ÀÚ°Ý ¿ä°Ç ◾ÃÑ º¸À¯°æ·Â: 3³â ÀÌ»ó ◾ÇзÂ/Àü°ø: ¼®»ç ÀÌ»ó, ÄÄÇ»ÅÍ °øÇÐ °ü·Ã Àü°øÀÚ ¿ì´ë ◾±âŸ -Python(strongly preferred), Scala, SQL, Hadoop, Docker »ç¿ë °æÇè(¿ì´ë) -Spark, Hive, Kafka, Airflow, Gitlab-CI »ç¿ë °æÇè(¿ì´ë) 4. ä¿ëÀýÂ÷ ◾¼·ù°ËÅä ¡æ ÄÚµùÅ×½ºÆ® ¡æ Å×ÀÌÅ© Ȩ ÇÁ·ÎÁ§Æ® ¡æ ±â¼ú¸éÁ¢ ¡æ ÀÓ¿ø¸éÁ¢ 5.Áö¿ø¹æ¹ý ◾´ç»ç ȨÆäÀÌÁö ¿Â¶óÀÎ Áö¿ø https://tas-sktelecom.taleo.net/careersection/ex/jobdetail.ftl -ÀÚ¼¼ÇÑ »ó¼¼¿ä°Àº ¹Ýµå½Ã ä¿ë ȨÆäÀÌÁö¿¡¼ Á÷Á¢ È®ÀÎÇϽñ⠹ٶø´Ï´Ù. |