Jobs
Required Skills
Machine Learning
Python
Data Analysis
Problem Solving
Engineering
Scopely is looking for a Machine Learning Engineer to join our Live Ops 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 Live Ops 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 Live Ops Automation team, you will:
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Gain an understanding of how games operate, how they are designed, and how they keep their audience engaged over time.
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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.
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Transform and analyze player data to validate assumptions, understand user behaviour, and develop algorithmic/ML solutions.
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Work together, as one team: communicate clearly, ask for help early, and proactively support others.
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Collaborate with MLEs, Engineering Managers, and Product Managers to implement improvements across the team and portfolio.
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Build and maintain cloud-native infrastructure for model training and serving.
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Implement tools that empower Live Ops and Game Design teams to create new and exciting gameplay experiences.
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Support and troubleshoot the Live Ops 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:
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Proactive, creative problem-solver: you enjoy tackling ambiguous problems and “figuring it out” with practical solutions.
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Strong team player: You collaborate openly, share context, and help others succeed.
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Hands-on experience implementing solutions using algorithms, heuristics, machine learning, and analytical approaches.
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Pragmatic engineering mindset: you know when to take shortcuts, and that done is better than perfect.
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Strong technical background: engineering, computer science, machine learning, mathematics, statistics, or equivalent.
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Strong coding skills in at least one mainstream language (Python, Java, C++)
Bonus Points
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Experience in the gaming industry.
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Experience with Airflow and dbt.
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Experience in A/B testing (design, analysis, guardrails, pre-test bias, significance), causal inference, and Bayesian statistics.
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Experience delivering ML products (batch and real-time serving, monitoring, alerting, automated unit, integration, and end-to-end tests).
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Experience with a major cloud provider (AWS / Azure / GCP).
Please ensure that the résumé/CV you attach is written in English.
About Scopely
Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play.
Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the Fox Next, GSN, and Niantic games businesses — Scopely consistently delivers experiences players love today and return to for years to come.
Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play.
Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit: https://www.scopely.com/.
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About Scopely

Scopely
AcquiredScopely is a mobile gaming company that develops and publishes free-to-play games for smartphones and tablets. The company operates popular game franchises including Star Trek Fleet Command, Marvel Strike Force, and Stumble Guys.
1,001-5,000
Employees
Culver City
Headquarters
$4.9B
Valuation
Reviews
4.2
5 reviews
Work Life Balance
4.0
Compensation
3.8
Culture
4.2
Career
2.5
Management
2.8
Pros
Great benefits and competitive compensation
Amazing people and passionate team members
Flexible work from home options
Cons
Very difficult career growth and promotion opportunities
Company becoming too big and corporate
Poor communication and slow processes
Salary Ranges
131 data points
Junior/L3
Junior/L3 · Business Analyst
0 reports
$41,386
total / year
Base
-
Stock
-
Bonus
-
$35,178
$47,594
Interview Experience
4 interviews
Difficulty
3.3
/ 5
Duration
14-28 weeks
Offer Rate
25%
Experience
Positive 0%
Neutral 0%
Negative 100%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Multiple Technical Interviews
5
HR Screening
6
Take-home Assignment
7
Offer
Common Questions
Technical Knowledge
Coding/Algorithm
Behavioral/STAR
System Design
Past Experience
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