Toss Securities Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer Experienced in - Python (including Numpy, Pandas, Pytorch) - Machine Learning - Large Language Model - Workflow management tools (Airflow, Argo Ecosystem) - Infrastructures (docker, K8S, RDBMS, MongoDB, Redis) - Hadoop ecosystem (hive, impala, presto)
Seoul National University
Master of Science (MS), Computer Science
January 1, 2010 – January 1, 2011
Korea Advanced Institute of Science and Technology
Bachelor of Science (BS), computer science
January 1, 2006 – January 1, 2009
Toss Securities
Machine Learning Engineer
May 1, 2022 – Present
대한민국 서울
NAVER Corp
Software Engineer
August 1, 2017 – May 1, 2022
Seongnam, South Korea
Solidware Co., Ltd.
Machine Learning Scientist
October 1, 2015 – July 1, 2017
Seoul, South Korea
ETRI
Researcher
March 1, 2012 – September 1, 2015
Daejeon, South Korea
Cultural Fit Analysis
The candidate has worked in diverse environments ranging from large corporations (NAVER Corp) to startups (Toss Securities, Solidware Co., Ltd.) and research institutions (ETRI). This breadth of experience suggests adaptability to different organizational cultures. Their focus on practical application of ML in various domains (e-commerce, finance, wearable tech) indicates a problem-solving mindset that would likely fit well into an innovative and results-driven culture.
Soft Skills & Operational Fit
The candidate's resume indicates a strong focus on technical roles and research. While direct evidence of soft skills like teamwork or leadership is not explicitly detailed, the nature of their roles in developing complex systems and platforms suggests an ability to collaborate and execute. Operational fit appears strong given the direct alignment of their experience with Machine Learning Engineer roles.