Job Opportunities API

THE COMPANY KRAFTON is dedicated to identifying and publishing games worldwide that offer a uniquely enjoyable experience, crafted by our globally recognized production studios known for their distinctive creativity. We continuously push the boundaries of gaming enjoyment by embracing new challenges and technologies and expanding our platforms and services to captivate an even larger fan base. Best known for the genre-defining worldwide sensation PUBG: Battlegrounds, our stellar studios based across the globe include PUBG Studios, Striking Distance Studios, Unknown Worlds, Bluehole Studio, RisingWings and more. In collaboration with our passionate and driven team, we strive to establish ourselves as a renowned creator of masterpieces in the global gaming market. THE OPPORTUNITY We develop, apply, and operate game security solutions and security operations systems to create a trusted gameplay environment for KRAFTON games.  Centered around KRAFTON Security Services (KSS), we provide core capabilities and services required for game security, including Anti-Cheat, Anti-Tamper, security operations, data analysis, and ML-based detection. DUTIES   Enhance the data analytics and ML-based detection capabilities provided by KSS, and develop models that can quickly and accurately detect and classify abnormal behavior and cheating in games. You will analyze large-scale game logs and user behavior data, improve the performance of detection models, and support the effective use of detection results in security operations and enforcement response. RESPONSIBILITIES Develop and improve ML models to detect abnormal user behavior and cheating in games Detect anomalies by analyzing large-scale game logs, user behavior data, and security events Analyze cheating patterns, identify detection features, and design and enhance detection logic Support data analysis for security operations and enforcement response Design and visualize metrics to improve KSS detection and operational efficiency Collaborate with game studios, security engineers, and other stakeholders Evaluate detection model performance, analyze false positives and false negatives, and improve model quality QUALIFICATIONS Degree in a related field such as Machine Learning, Deep Learning, Statistics, or Computer Science, or equivalent practical experience Experience with ML-based modeling projects such as anomaly detection, classification, prediction, or pattern analysis within a gameplay environment Ability to analyze large-scale log and event data using Python, SQL, or similar tools Understanding of the end-to-end data workflow, including log data cleansing, feature engineering, training data construction, and model evaluation Experience understanding the structure of machine learning/deep learning models and improving models according to their objectives Ability to perform feature engineering with consideration for data quality, reproducibility, and scalability Ability to quantitatively evaluate model performance and identify improvement directions from the perspective of false positives and false negatives Ability to define problems independently and drive improvements based on data PREFERRED QUALIFICATIONS Experience using game data for Anti-Cheat, cheating/abuse detection, or abnormal behavior analysis Gameplay experience in various game genres such as FPS/TPS, battle royale, or MMORPG, or understanding of the data characteristics of these genres Experience detecting abnormal patterns based on user behavior data and improving models or detection logic Experience processing large-scale log data and building or operating ML pipelines Experience using, or understanding of, large-scale data platforms such as Spark and Hadoop Experience collaborating with global organizations/studios, or communication skills in Korean or a se