About the Role We are building a next-generation AI-driven anti-cheating system for competitive strategy games.
Unlike traditional fraud detection, our challenge sits at the intersection of:
🎮 Game AI & player behavior modeling
🧠 Reinforcement learning & decision systems
🔍 Anomaly detection under adversarial conditions
You will work on identifying non-obvious, strategic cheating behaviors in complex environments where players actively adapt to detection systems. This is not rule-based detection — this is behavioral intelligence at scale.
What You’ll Do 1️⃣ Behavioral Modeling & Detection
Design machine learning / deep learning models to detect cheating patterns
Model player behavior sequences, strategies, and anomalies
Build systems that distinguish:
high-skill play vs. AI-assisted play
natural variance vs. exploitation
2️⃣ Anti-Cheating System Design
Develop scalable detection pipelines (offline + real-time)
Build feature systems from gameplay logs / event streams
Design evaluation frameworks for detection accuracy & robustness
3️⃣ ML / DL / Advanced Techniques
Apply and experiment with:
sequence modeling (RNN / Transformer-based)
anomaly detection
graph-based or behavioral embeddings
Explore intersections with:
reinforcement learning
game-theoretic modeling
adversarial ML
4️⃣ Collaboration with AI & Engineering Teams
Work closely with:
Gameplay AI / RL researchers
Backend / data engineering teams
Translate models into production systems
What We’re Looking For
✅ Core Requirements
4+ years in Data Science / Machine Learning roles
Strong foundation in:
deep learning
statistical modeling
Experience in one or more of:
fraud detection / AML
risk modeling
anomaly detection
behavioral analytics
✅ Strong Signals (Big Plus)
Experience with:
sequence models (LSTM / Transformer)
large-scale behavioral data
real-time detection systems
Exposure to:
reinforcement learning
game AI
adversarial systems
✅ Technical Stack
Python (must)
PyTorch / TensorFlow
SQL / data pipelines
Experience working with large-scale datasets
Why This Role is Interesting
🚀 Work on problems similar to fraud detection at scale — but harder
🎯 Direct impact on real-money / competitive environments
🧠 Blend of:
ML research
production systems
game AI
🌍 Fully remote, globally distributed team
Location & Visa
🌏 Remote-first (global team)
🇯🇵 Japan relocation supported (visa sponsorship available for qualified candidates)
Who This Role is Perfect For
Data scientists bored with “dashboard ML”
Fraud / AML experts who want more complex, adversarial systems
ML engineers who want to work closer to decision intelligence & behavior modeling