SENIOR MACHINE LEARNING ENGINEER - LIVEOPS AUTOMATION TEAM

Description Scopely is looking for a Senior Machine Learning Engineer to join our LiveOps Automation team in Spain on a hybrid or remote basis.
At Scopely, we care deeply about what we do and want to inspire play every day - whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players.
We are a global team of game lovers who are developing, publishing and innovating the mobile games industry, connecting millions of people worldwide daily.
Scopely's Midcore Division operates the award winning and industry leading Star Trek Fleet Command, Marvel Strike Force and WWE Champions games.
We're moving cross platform and have two exciting and ambitious games in development to further strengthen our position and reputation within the industry.
What You Will Do You'll be joining the LiveOps Automation team at Scopely.
We are responsible for building a sophisticated suite of LiveOps tools driven by Machine Learning (ML) automation and decision-making.
This will change how Midcore manages its games in the future.
We are looking for a creative and highly motivated Senior ML Engineer to join the Scopely LiveOps Automation Team.
This role will focus on unleashing ML capabilities for LiveOps teams that work on different gaming platforms.
Contribute to technical plans, discussing areas of opportunity and requirements with stakeholders Define the team's roadmap and vision for ML within the Mid-Core division.
Serve as a role model for less experienced team members.
Validate data science prototypes with stakeholders and transform them into production-usable ML models.
Building and maintaining cloud-native infrastructure for hyperscale ML models training and serving.
Work with other developers to implement tools to empower our Live Operators and Game Design teams to create new and exciting game-play experiences.
LiveOps Automation toolsuite support & troubleshooting.
What We're Looking For A deep understanding of ML technologies development and best practices Highly experienced delivering production quality, highly performant ML platforms Experience with machine Learning Frameworks (PyTorch, MXNet, Tensorflow, etc.) and model serving frameworks (Seldon Core, TorchServe, TensorFlow Serving, etc.) Very strong coding ability, and experience in development in at least one mainstream programming language (Python, Java, C++ etc.) and with at least one major public cloud provider (AWS / Azure / GCP) Experience writing and maintaining automated unit, integration, and end-to-end tests Bonus Points Experience building, managing, and maintaining MLOps platforms Experience in at least one of the following.
Amazon Redshift, Google BigQuery, or Azure SQL Data Warehouse Experience building recommendation systems You've mentored less experienced team members About Us Scopely is a global interactive entertainment and mobile-first video game company, home to many top, award-winning experiences such as "MONOPOLY GO!," "Star Trek™ Fleet Command," "Stumble Guys," "MARVEL Strike Force," and "Yahtzee® With Buddies," among others.
Scopely creates, publishes, and live-operates immersive games that empower a directed-by-consumer™ experience across multiple platforms--from mobile, web, PC and beyond.
Founded in , Scopely is fueled by a world-class team and a proprietary technology platform, Playgami, that supports one of the most diversified portfolios in the games industry.
Recognized multiple times as one of Fast Company's "World's Most Innovative Companies," Scopely is a multi-billion-dollar business due to its ability to create long-lasting game experiences that players enjoy for years.
Scopely has global operations in more than a dozen markets across Asia, EMEA, and North America, and is home to many internal game development teams, referred to as Scopely Studios, with additional game studio partners across four continents.
Scopely was acquired by Savvy Games Group in July for $4.
billion, and is now an independent subsidiary of Savvy.
For more information on Scopely, visit.
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