Senior Machine Learning Engineer - Anomaly Detection

Role overview: The candidate will design, implement and optimize novel anomaly/glitch detection algorithms to automatically identify bugs and glitches in games. You will lead research workstreams, publish papers, file patents, and present at internal and academic conferences. You will collaborate with cross-functional teams to deploy ML models in production, ensuring scalability and performance. You will mentor junior team members and partners in industry-academia collaborations. You will communicate complex technical findings to varied audiences and stay current with the latest AI research, prototyping rapidly to evaluate new ideas. Requirements: Master’s degree in computer science, machine learning, electrical engineering, robotics, statistics, mathematics, or a related field; PhD preferred but can be substituted with relevant work experience. 5+ years of relevant work or research experience in ML/AI or game development. Domain expertise in anomaly detection for QA, gameplay analysis, computer vision, or video stream analysis, preferably in a studio environment. Proficiency in Python and ML frameworks such as TensorFlow or PyTorch. Strong data analysis, signal processing, and statistical modelling skills. Experience in game development and exposure to self-supervised learning, multimodal or vision-language models is a plus. Excellent problem-solving, communication, and teamwork abilities, with a passion for gaming and a drive to publish at top conferences. Hybrid/remote work available.