Artificial Intelligence Engineer
hace 4 semanas
Overview
Scopely is seeking a Machine Learning Engineer to enhance our LiveOps Automation team. This role can be performed in a hybrid or remote setting. At Scopely, we are passionate about our mission and strive to inspire play every day, whether through our collaborative workspaces or our strong ties with our player communities. Our global team of gaming enthusiasts is dedicated to developing, publishing, and innovating within the mobile gaming sector, engaging millions of players worldwide.Responsibilities
Focus on leveraging ML capabilities for LiveOps teams across various gaming platforms. Engage in the design, development, and research of ML systems, models, and methodologies, while collaborating with stakeholders to refine workflows and requirements. Contribute to the creation of an advanced suite of LiveOps tools powered by Machine Learning automation and decision-making, fundamentally transforming the management of MidCore games. Convert data science prototypes into production-ready ML models, ensuring their performance is maintained over time. Develop and sustain cloud-native infrastructure for high-scale ML model deployment. Collaborate with fellow developers to create tools that empower our Live Operators and Game Design teams, enhancing gameplay experiences and providing support for the LiveOps Automation tool suite. Participate in the formulation of technical plans and engage in discussions regarding workflows and requirements with stakeholders.Qualifications
Profound knowledge of ML technology development and industry best practices. Extensive experience in delivering high-quality, efficient ML platforms. Familiarity with machine learning frameworks such as PyTorch, MXNet, TensorFlow, and model serving frameworks like Seldon Core, TorchServe, TensorFlow Serving. Strong programming skills with experience in at least one major programming language (Python, Java, C++) and proficiency with at least one leading cloud service provider (AWS, Azure, GCP). Proven experience in writing and maintaining automated unit, integration, and end-to-end tests.Preferred Skills
Experience in building, managing, and maintaining MLOps platforms. Knowledge of data warehousing solutions such as Amazon Redshift, Google BigQuery, or Azure SQL Data Warehouse. Experience in developing recommendation systems. A track record of mentoring junior team members.-
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