Machine Learning Engineer - LiveOps Automation
Scopely is looking for a Machine Learning Engineer to join our LiveOps Automation team in Spain on a 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.
The LiveOps Automation team builds a suite of ML powered tools to enhance player experiences across Scopely’s Live Games Portfolio. This initiative has a long term impact on how games are operated, how game economies are balanced, and the experience of millions of daily active players.
What You Will Do
In the LiveOps Automation team, you will:
Gain an understanding of how games operate, how they are designed, and how they keep their audience engaged over time.
Support ML projects end-to-end: from business requirements with stakeholders to technical specs, solution design/validation, data modeling, algorithmic/ML, prototyping, A/B testing, deployment, monitoring, and iteration.
Transform and analyze player data to validate assumptions, understand user behaviour, and develop algorithmic/ML solutions.
Work together, as one team: communicate clearly, ask for help early, and proactively support others.
Collaborate with MLEs, Engineering Managers, and Product Managers to implement improvements across the team and portfolio.
Build and maintain cloud-native infrastructure for model training and serving.
Implement tools that empower LiveOps and Game Design teams to create new and exciting gameplay experiences.
Support and troubleshoot the LiveOps Automation tool suite.
What We're Looking For
We are looking for a creative and highly motivated ML Engineer with experience in most of the following areas:
Proactive, creative problem-solver: you enjoy tackling ambiguous problems and “figuring it out” with practical solutions.
Strong team player: You collaborate openly, share context, and help others succeed.
Hands-on experience implementing solutions using algorithms, heuristics, machine learning, and analytical approaches.
Pragmatic engineering mindset: you know when to take shortcuts, and that done is better than perfect.
Strong technical background: engineering, computer science, machine learning, mathematics, statistics, or equivalent.
Strong coding skills in at least one mainstream language (Python, Java, C++)
Bonus Points
Experience in the gaming industry.
Experience with Airflow and dbt.
Experience in A/B testing (design, analysis, guardrails, pre-test bias, significance), causal inference, and Bayesian statistics.
Experience delivering ML products (batch and real-time serving, monitoring, alerting, automated unit, integration, and end-to-end tests).
Experience with a major cloud provider (AWS / Azure / GCP).
Please ensure that the résumé/CV you attach is written in English.
About the job
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Machine Learning Engineer - LiveOps Automation
Scopely is looking for a Machine Learning Engineer to join our LiveOps Automation team in Spain on a 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.
The LiveOps Automation team builds a suite of ML powered tools to enhance player experiences across Scopely’s Live Games Portfolio. This initiative has a long term impact on how games are operated, how game economies are balanced, and the experience of millions of daily active players.
What You Will Do
In the LiveOps Automation team, you will:
Gain an understanding of how games operate, how they are designed, and how they keep their audience engaged over time.
Support ML projects end-to-end: from business requirements with stakeholders to technical specs, solution design/validation, data modeling, algorithmic/ML, prototyping, A/B testing, deployment, monitoring, and iteration.
Transform and analyze player data to validate assumptions, understand user behaviour, and develop algorithmic/ML solutions.
Work together, as one team: communicate clearly, ask for help early, and proactively support others.
Collaborate with MLEs, Engineering Managers, and Product Managers to implement improvements across the team and portfolio.
Build and maintain cloud-native infrastructure for model training and serving.
Implement tools that empower LiveOps and Game Design teams to create new and exciting gameplay experiences.
Support and troubleshoot the LiveOps Automation tool suite.
What We're Looking For
We are looking for a creative and highly motivated ML Engineer with experience in most of the following areas:
Proactive, creative problem-solver: you enjoy tackling ambiguous problems and “figuring it out” with practical solutions.
Strong team player: You collaborate openly, share context, and help others succeed.
Hands-on experience implementing solutions using algorithms, heuristics, machine learning, and analytical approaches.
Pragmatic engineering mindset: you know when to take shortcuts, and that done is better than perfect.
Strong technical background: engineering, computer science, machine learning, mathematics, statistics, or equivalent.
Strong coding skills in at least one mainstream language (Python, Java, C++)
Bonus Points
Experience in the gaming industry.
Experience with Airflow and dbt.
Experience in A/B testing (design, analysis, guardrails, pre-test bias, significance), causal inference, and Bayesian statistics.
Experience delivering ML products (batch and real-time serving, monitoring, alerting, automated unit, integration, and end-to-end tests).
Experience with a major cloud provider (AWS / Azure / GCP).
Please ensure that the résumé/CV you attach is written in English.