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채용Scopely

Machine Learning Engineer - LiveOps Automation

Scopely

Machine Learning Engineer - LiveOps Automation

Scopely

ES - Spain

·

On-site

·

Full-time

·

1mo ago

필수 스킬

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:

  • 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 Live Ops and Game Design teams to create new and exciting gameplay experiences.

  • 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:

  • 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 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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Scopely 소개

Scopely

Scopely

Acquired

Scopely, Inc. is an American video game developer and publisher. The company is headquartered in Culver City, California, with offices across North America, Central America, EMEA and Asia, with its largest location in Barcelona, Spain.

1,001-5,000

직원 수

Culver City

본사 위치

$4.9B

기업 가치

리뷰

4.2

5개 리뷰

워라밸

4.0

보상

3.8

문화

4.2

커리어

2.5

경영진

2.8

장점

Great benefits and competitive compensation

Amazing people and passionate team members

Flexible work from home options

단점

Very difficult career growth and promotion opportunities

Company becoming too big and corporate

Poor communication and slow processes

연봉 정보

131개 데이터

Junior/L3

L3

Intern

Junior/L3 · Data Analyst

0개 리포트

$43,910

총 연봉

기본급

-

주식

-

보너스

-

$37,324

$50,496

면접 경험

4개 면접

난이도

3.3

/ 5

소요 기간

14-28주

합격률

25%

경험

긍정 0%

보통 0%

부정 100%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Multiple Technical Interviews

5

HR Screening

6

Take-home Assignment

7

Offer

자주 나오는 질문

Technical Knowledge

Coding/Algorithm

Behavioral/STAR

System Design

Past Experience