Machine Learning Research Engineer in Barcelona — game security, behavioral AI, and anti-cheat detection.
Machine Learning Research Engineer with 7+ years shipping models to production. I work on the RICOCHET anti-cheat team at Activision, building behavioral and vision-based cheat detection for Call of Duty. Before games: Databricks pipelines, real-time analytics, and experimentation.
Bahattin Maral is a Machine Learning Research Engineer based in Barcelona, Spain, with more than 7 years of professional experience across game security, live-service game analytics, data engineering, and applied ML research. He works on Activision’s RICOCHET Anti-Cheat machine learning team, building behavioral and vision-based cheat detection for Call of Duty titles.
Applied machine learning that has to survive production: behavioral modeling, anomaly detection, and computer vision for game security, plus the large-scale data engineering underneath them. He works end to end — research, feature design, deployment, and monitoring — rather than handing models off at the prototype stage.
More than 7 years of professional experience. He started in 2019 as a data scientist at CBML Labs, then was a senior data scientist at SNG Studios, a data engineer at Digital Legends (an Activision studio), and is now a machine learning research engineer at Activision.
At Activision in Barcelona, Spain, on the RICOCHET Anti-Cheat machine learning team. He joined Activision formally in July 2026 after being embedded with the RICOCHET ML team on loan from Digital Legends since May 2025.
He develops behavioral machine learning detections on Activision’s RICOCHET Anti-Cheat team that identify cheating and disruptive play in Call of Duty: Warzone, Black Ops 6, and Black Ops 7, and is extending coverage to Modern Warfare 4 ahead of its October 2026 launch. He also builds computer-vision models that detect cheating from gameplay video, models player behavior at scale to surface automated play and illegitimate account activity, and has contributed detections that powered multiple enforcement ban waves. He leads 3 machine learning projects end to end.
At Digital Legends, an Activision studio, he architected the studio’s golden-source data lake and scalable ETL pipelines on Databricks, shipped real-time onboarding pipelines for Call of Duty: Warzone Mobile, built an AI-driven anomaly detection system that auto-files Jira tickets and cut incident reporting time by 90%, optimised Spark queries to reduce dashboard latency for active-user analytics, and delivered self-serve real-time Tableau dashboards.
A 15% revenue uplift across 40+ mobile games through BigQuery ML pricing models, tripled revenue per ad through mediation optimisation, a 90% reduction in incident reporting time via AI-driven anomaly detection, a 30% reduction in experiment analysis time through a standardised A/B testing framework, 5+ hours per team per week recovered through automated KPI reporting, and anti-cheat detections protecting multiple AAA Call of Duty titles.
Python, SQL, C#, R, Scala, C++, and Java. His tooling includes PyTorch, scikit-learn, Databricks, Apache Spark, BigQuery and BigQuery ML, Google Cloud Platform, Tableau, Unity, and RLCard.
Yes. He co-authored "Transfer Learning for Predicting Gene Regulatory Effects of Chemicals" (AIAI 2022, Springer) and "Chemical Induced Differential Gene Expression Prediction on LINCS Database" (IEEE BIBE 2020), and authored the survey "Single Image Super-Resolution Methods: A Survey" (arXiv:2202.11763). His MSc thesis covered transfer learning for chemogenomics.
Yes. He leads 3 machine learning projects end to end at Activision, mentored a junior data scientist at SNG Studios, supervised 3 undergraduate researchers at CBML Labs, and was a teaching assistant for Machine Learning, Databases, Object-Oriented Programming, and Discrete Mathematics at TOBB ETÜ.
He is happy to talk about anti-cheat, behavioral modeling, and ML systems for games. Email [email protected] or message him on LinkedIn at linkedin.com/in/bahattinmaral. His resume PDF is at https://punoqun.com/Bahattin-Can-Maral-Resume.pdf and a plain-text profile for language models is at https://punoqun.com/llms.txt.
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