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Machine Learning Engineer [Game Intelligence]

Company Description

Massive Entertainment is a world-leading AAA studio located in Malmö, Sweden and part of the Ubisoft family. We’re a multinational team of more than 750 passionate and highly skilled people from 50+ different countries. Our studio’s goal has always been – and still is – to craft the finest gaming experiences for all players. 

At Massive, you get to do what you love most while bringing your own experience to our ongoing projects, like Tom Clancy’s The Division 2, Avatar: Frontiers of Pandora, and Star Wars Outlaws. We're also developing new tech here, such as our in-house engine Snowdrop, and Ubisoft Connect - Ubisoft's digital ecosystem and distribution platform. 

Job Description

We're looking for a Machine Learning Operations Engineer to join our Game Intelligence Department, to help us continue enabling advanced data processing solutions, that contribute making better games within our world class videogame studio. 

As a MLOps Engineer, you’ll be responsible for designing, implementing and maintaining data pipelines and infrastructure for ML models industrialization, together with corresponding data pipelines, data analysis and performance monitoring tooling. It includes developing solutions and tooling for monitoring ETLs, data quality and ML models performance, as well as troubleshooting and fixing issues. 

You'll collaborate with Data Scientists, Data Engineers, Game Analysts, Ubisoft tech providers teams and IT Support, to understand the needs and propose robust, player-facing operational ML solutions that answers the business requirements, in a complex technical environment. 

Some of the areas you'll be focusing on are: 

  • Supporting the game intelligence ETLs & infrastructure needs for game productions; 
  • Developing tools, libraries and frameworks to enable ML-based use cases running smoothy in production environment; 
  • Industrialize prototypes of advanced data processing solutions developed in the team 

We're offering a permanent position in Malmö, Sweden, with the flexibility to work partially from home (up to two days a week) under our Flexible Workplace Policy. Please apply using English, our company's primary language. 
 

What You’ll Do 

  • Create and maintain optimal data pipelines and ML models management solutions in an industrialized setup, in collaboration with Massive and Ubisoft data and infrastructure teams. Improve pre-existing solutions, and whenever applicable, manage their re-engineering through structured transitioning. 
  • Lead the assembly of large datasets and high-performance ML models from heterogeneous data sources, fulfilling business, technical and performance constraints. 
  • Identify, design, implement and maintain monitoring tools, CI/CD automation pipelines, industry-grade unit tests or any relevant solution helping to ensure data quality, robustness, and resilience. Perform related incident investigations.  
  • Participate in industrialization of prototypes developed by the team, into scalable, robust solutions used by internal/external clients or applications. 
  • Contribute to defining the Game Intelligence dept’s data and MLOps infrastructure, standards and processes, in collaboration with other teams within the department, production teams, as well as Ubisoft-wide solutions teams. 
  • Work with stakeholders including the Management, Data Engineers, Analysts and Scientists, to assist with technical issues and support infrastructure needs. 
  • Stay connected with ongoing trends and technologies in your area of expertise, advocating for new and reliable solutions, promoting best practices at dept level. 
  • Communicate in a clear way all findings, situations and solutions to stakeholders, enabling effective decision-making. 
  • Contribute to the documentation of all processes, ETLs, ML models engineering, reports and tools, within the centralized dept documentation repository. 

Qualifications

What you’ll bring 

You’re motivated by how big amounts of data, efficient ML operations and production-grade code can support pre-launch or live games, and comfortable in a variety of ML frameworks and technologies. You're interested in video games and are motivated by collaborating with a team for high-quality deliveries and support. You are curious by heart and thrive in finding new possible ways and solutions to enhance your work. You communicate efficiently and create trustful relations with your stakeholders, while focusing on production's needs. 

Besides the above we’re looking for someone aligned with our core values  and the following skills and experience: 

  • Proven work experience in MLOps and data engineering, with a wide range of machine learning frameworks, and software engineering best practices 
  • Proficient in Python, SQL, PySpark 
  • Proficient with various cloud services and large-scale distributed architectures, examples of which are Hadoop or Spark; A ‘plus’ for experience with Databricks. 
  • Proficient with development / version control tools and IDEs such as Gitlab, VSCode, Docker, CI-CD, orchestration (Airflow), etc. 
  • Experience working with supervised & unsupervised ML algorithms, such as recommendation systems or clustering techniques 
  • Key analytic skills and video game data domain curiosity; 
  • A master’s degree in Computer Science, Machine Learning, Data Science, a similar field, or the equivalent work experience. 
  • Experience working within the game development industry, and interest or knowledge in games developed at Massive is beneficial 

 

Additional Information

Ubisoft’s 19,000 team members, working across more than 30 countries around the world, are bound by a common mission to enrich players’ lives with original and memorable gaming experiences. Their commitment and talent have brought to life many acclaimed franchises such as Assassin’s Creed, Far Cry, Watch Dogs, Just Dance, Rainbow Six, and many more to come. Ubisoft is an equal opportunity employer that believes diverse backgrounds and perspectives are key to creating worlds where both players and teams can thrive and express themselves. If you are excited about solving game-changing challenges, cutting edge technologies and pushing the boundaries of entertainment, we invite you to join our journey and help us create the unknown. 

You can also find a summary of the Massive Job Perks here. 

Questions? We're more than happy to answer them! Please contact Paula Roese Mesquita

All your application information will be kept confidential according to EEO & GDPR guidelines. 

What You Should Know About Machine Learning Engineer [Game Intelligence], Ubisoft

Are you ready to join a leading AAA studio and make your mark in the world of gaming? Massive Entertainment in Malmö, Sweden, is on the lookout for a passionate Machine Learning Engineer to join our Game Intelligence Department! Picture yourself designing and maintaining cutting-edge data pipelines and infrastructure that power our incredible games, such as Tom Clancy’s The Division 2 and Avatar: Frontiers of Pandora. You’ll collaborate with a diverse team of Data Scientists, Engineers, and Analysts, all striving to develop operational ML solutions that enhance the gaming experience for players around the globe. In this role, you’ll be tasked with creating and optimizing ML models, ensuring data quality, and monitoring performance in a dynamic environment. You’ll have the opportunity to support game productions by improving existing solutions and driving innovation through robust tooling. Ready to take your career to the next level? At Massive, you can enjoy a flexible working environment, with the option to work from home up to two days a week. Join us, and let's craft unforgettable gaming experiences together!

Frequently Asked Questions (FAQs) for Machine Learning Engineer [Game Intelligence] Role at Ubisoft
What are the main responsibilities of a Machine Learning Engineer at Massive Entertainment?

As a Machine Learning Engineer at Massive Entertainment, your main responsibilities will include designing and maintaining data pipelines for ML models, developing monitoring tools for data quality, collaborating with various teams to support game intelligence, and industrializing prototypes into scalable solutions. You will also communicate findings to stakeholders and stay updated on industry trends.

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What qualifications are needed for the Machine Learning Engineer position at Massive Entertainment?

To qualify for the Machine Learning Engineer position at Massive Entertainment, candidates should have proven experience in MLOps, data engineering, and proficiency in Python and SQL. A master’s degree in relevant fields like Computer Science or Data Science is important. Knowledge of supervised/unsupervised ML algorithms and experience in the gaming industry are beneficial.

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How does the Machine Learning Engineer role contribute to game production at Massive Entertainment?

The Machine Learning Engineer role is crucial to game production at Massive Entertainment as it enables advanced data processing solutions that improve gameplay. By optimizing ML models and ensuring data quality, the engineer contributes to delivering a smooth and engaging gaming experience for players.

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What technologies and tools will a Machine Learning Engineer use at Massive Entertainment?

A Machine Learning Engineer at Massive Entertainment will utilize various technologies and tools, including Python, SQL, PySpark, and cloud services like Hadoop or Spark. Proficiency in development tools like GitLab, Docker, and orchestration tools like Airflow is also essential.

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Can you describe the work culture at Massive Entertainment as a Machine Learning Engineer?

The work culture at Massive Entertainment is collaborative and inclusive, fostering innovation and creativity. As a Machine Learning Engineer, you'll work with a multinational team, have flexible working options, and be encouraged to contribute your ideas to enhance gaming experiences. The studio values continuous learning and staying connected with industry advancements.

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Common Interview Questions for Machine Learning Engineer [Game Intelligence]
Can you describe your experience with MLOps and how it applies to game development?

When discussing your MLOps experience, focus on specific projects where you designed and managed ML pipelines. Highlight instances where your contributions led to tangible improvements in game performance or player experience, showcasing your technical skills and understanding of the gaming industry.

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What tools and technologies are you proficient in as a Machine Learning Engineer?

Be prepared to discuss your experience with Python, SQL, and cloud services. Describe how you've utilized tools like Docker, GitLab, or CI/CD pipelines to streamline ML workflows. Specific examples of projects where you effectively employed these technologies can strengthen your answer.

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How do you ensure the quality of the data in your ML models?

Explain the processes you implement for data validation and quality assurance, including monitoring ETLs and maintaining data integrity. Share examples where you identified issues in datasets and resolved them, explaining the impact these actions had on your models' performance.

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What approaches do you take to optimize ML models for production?

Detail your strategies for optimizing ML models, such as feature engineering, hyperparameter tuning, or selecting the right algorithms. Provide examples where you successfully improved model performance, particularly within a gaming context.

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Can you describe your experience with supervised and unsupervised learning algorithms?

Discuss your hands-on experience with both supervised and unsupervised learning. Share specific algorithms you’ve implemented, potentially in the context of game recommendation systems or clustering techniques, demonstrating your ability to apply theoretical knowledge to practical scenarios.

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How do you stay updated with the latest trends and technologies in ML and gaming?

Emphasize your commitment to professional development and staying informed about industry advancements. Mention blogs, conferences, courses, or communities you engage with that focus on machine learning and gaming technology.

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Describe a challenging ML problem you faced and how you solved it.

Choose a specific example of a difficult ML challenge, such as an underperforming model or data quality issue. Explain the steps you took to analyze the situation, the solutions you implemented, and the end results, showcasing your problem-solving skills.

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How do you prioritize tasks when managing multiple projects?

Outline your approach to task management and prioritization, emphasizing your organizational skills and the tools you use. Stress the importance of communication with stakeholders to understand project impact and urgency.

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What is your experience working with game data, and how do you leverage it in ML operations?

Discuss any experience you have with game data analytics, explaining how you've used data insights to inform ML model development. Provide examples of specific metrics or player behaviors you've analyzed to enhance gameplay experiences.

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How do you ensure effective communication with non-technical stakeholders?

Stress the importance of clear and concise communication. Give examples of how you've previously conveyed complex technical concepts to non-technical team members, ensuring they understand the implications of your findings and solutions.

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At Ubisoft, we are dedicated to enriching players' lives with original and memorable moments of play.

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Full-time, hybrid
DATE POSTED
March 21, 2025

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