Key job responsibilities Design, develop, and deploy machine learning models and algorithms that solve critical problems for game developers, including player analytics, game performance optimization, content personalization, and fraud detection Lead end-to-end ML projects from problem definition through production deployment, ensuring solutions are scalable, maintainable, and deliver measurable business impact Analyze large-scale gaming datasets to identify patterns, extract insights, and develop predictive models that improve game operations and player experience Collaborate with game studios and AWS service teams to understand their challenges, define requirements, and deliver ML solutions that integrate seamlessly with their workflows Establish and promote best practices for ML development, experimentation, and deployment within the team, including model evaluation, A/B testing, and monitoring Mentor and provide technical guidance to junior applied scientists and engineers, fostering a culture of innovation and technical excellence Stay current with the latest research in machine learning, gaming analytics, and related fields, and apply relevant advances to solve customer problems Communicate complex technical concepts and results to both technical and non-technical audiences, including senior leadership Contribute to the technical strategy and roadmap for ML capabilities in AWS GameTech About the team AWS GameTech Cortex is an applied science & ML team, that specializes in full stack data solutions for games. Basic Qualifications - 5+ years of building machine learning models for business application experience - 5+ years of applied research experience - Experience with popular deep learning frameworks such as MxNet and Tensor Flow.