A global leader in EdTech! We are looking for an 'ML Engineer' to lead AI modeling for new product and engine development based on 970 million learning behavior data to transform the future of AI education at Catch It Play.
We are looking for someone who has experience deploying recommendation, prediction, and generation models into production. In an environment with cumulative 2.6 million users and 973 million learning behavior data, Catch It aims to collaborate with those who will help advance educational AI from a tool level to a collaborator level.
• Someone who can consider both model performance improvements and constraints of the serving environment (latency, costs, etc.)
• Someone with communication skills capable of translating domain requirements into ML problems.
• Someone who is curious and willing to learn and expand into new technological areas (LLM, Reinforcement Learning, etc.).
• Someone with experience in a small team who has been able to set direction and execute independently.
A. Model Design, Development, and Operation (~60%)
• Design, develop and apply core ML models such as recommendation, matching, churn prediction, and generative content using learning, content, and user data.
• Responsible for the entire ML lifecycle: model training → evaluation → tuning → production deployment → monitoring → retraining.
• Lead the entire process from defining new ML problems, data collection, hypothesis setting, modeling, experimentation, to service application.
• Translate model performance metrics (Macro F1, NDCG, AUC, etc.) into business KPIs and connect them to user value.
B. Experimentation, Tools, Collaboration (~40%)
• Design and operate A/B testing, quantitatively measure and verify model impact against business KPIs.
• Stay updated with the latest ML, LLM, and generative AI technology trends, validate and implement them in applicable forms.
• Collaborate with data engineers to run Feature Store, model serving, and operational infrastructure together.
• Actively participate in defining ML requirements with PMs, planners, and analysts, and contribute to the team's technical decision-making.
• 5+ years of practical experience in ML/AI, with experience in deploying models in production.
• Experience in designing, training, tuning, and evaluating machine learning/deep learning models, and collaborating all the way to production application.
• Proficiency in Python (PyTorch, scikit-learn, etc.)
• Proficient in SQL and experienced in cloud environments (AWS/GCP/Azure).
• Experience in feature engineering based on large-scale behavioral logs or transaction data.
• Understanding of statistical hypothesis testing and experimental design (A/B testing, etc.).
• Experience in Git-based code collaboration and communications with domain experts and planners.
• Master's or higher in relevant fields such as Computer Engineering, Statistics, Mathematics, etc.
• Experience processing and modeling data at a scale of over 100 million records.
• Deep practical experience in specific fields such as recommendation systems, ranking, NLP, LLM, reinforcement learning, time series, and multimodal.
• Experience in research or implementation related to knowledge tracing, learner modeling, or educational AI.
• Experience in LLM applications (RAG, agents, fine-tuning, evaluation pipelines).
• Experience in designing and operating Feature Stores (Feast, Tecton, etc.).
• Experience in building or operating A/B testing platforms.
• Experience with MLOps pipelines (Airflow, MLflow, Kubeflow, etc.).
• Experience in domains based on behavioral logs such as EdTech, content recommendation, and gaming.
• Experience in publishing or presenting papers in relevant fields.
Benefits and Work Environment
• 🏠 Full remote work environment - A productive workspace based on full remote work that you can work from anywhere in the country.
• 📊 Stock option program - Stock options for core R&D personnel (grant review after 1 year of stable employment).
• 📈 Experience in global growth - Core experience in cutting-edge trend products that aim for 10 million downloads (like Google features).
• 💼 Experience in core system development - Direct involvement in the infrastructure and systems development in unique business core areas where games and AI converge.
• 🌴 Jeju Office & Refresh - Support refresh opportunities including working at the main office in Jeju.
• 📚 Self-development support - Support for self-development through books and online courses.
• 💪 Health management support - Support for health check-up costs / in-house health management programs.
• ❤️ Fun sports culture - We create a fun sports culture of competition and cooperation through monthly sports challenges.
• Required documents — Resume, cover letter, portfolio, or samples authored by you (clearly indicate the parts you worked on).
• Recruitment process — Document and portfolio review → 1st practical interview (online) → 2nd interview (online) → final interview (offline) → announcement of acceptance.
• There may be assignments (under 1 day) or tests during the interviews.
[For details, please refer to the Notion page below]
https://catchitplay.notion.site/AI-ML-36098f74ee5a80c0b70bf09ebdf98c3e
