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MLops 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 MLops Engineer [Game Intelligence], Ubisoft

At Massive Entertainment, a leading AAA studio within the Ubisoft family based in Malmö, Sweden, we're on the lookout for a passionate and skilled MLOps Engineer to join our talented Game Intelligence Department. If you're excited about the intersection of machine learning and gaming, this role is tailored for you! As an MLOps Engineer, you'll dive into a world where your expertise in data processing and ML operations is crucial for enhancing our gaming experiences. Imagine designing and maintaining robust data pipelines and infrastructure to bring operational ML solutions to life, supporting projects like Tom Clancy’s The Division 2 and Avatar: Frontiers of Pandora. You'll collaborate closely with Data Scientists and Engineers to transform ideas into reality, focusing on developing tools for monitoring data quality and model performance. Plus, with our flexible work arrangements, you'll be empowered to balance your professional and personal life seamlessly. If you're ready to contribute to awesome gaming experiences while growing in a vibrant team of over 750 people from diverse backgrounds, Massive is the place to be. Join us in pushing the boundaries of what's possible in gaming and technology!

Frequently Asked Questions (FAQs) for MLops Engineer [Game Intelligence] Role at Ubisoft
What are the responsibilities of an MLOps Engineer at Massive Entertainment?

As an MLOps Engineer at Massive Entertainment, you will take charge of designing, implementing, and maintaining data pipelines and the necessary infrastructure for machine learning models. Your primary responsibilities include supporting game intelligence ETLs, developing tools for monitoring ETLs and data quality, and troubleshooting issues to ensure robust operational ML solutions.

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What qualifications are needed to become an MLOps Engineer at Massive Entertainment?

To excel as an MLOps Engineer at Massive Entertainment, candidates should possess proven experience in MLOps and data engineering, along with proficiency in Python, SQL, and PySpark. A master’s degree in Computer Science, Machine Learning, Data Science, or a related field is preferred, although equivalent work experience will also be considered.

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What technologies does an MLOps Engineer at Massive Entertainment work with?

An MLOps Engineer at Massive Entertainment works with a variety of machine learning frameworks and cloud services. Familiarity with large-scale distributed architectures, such as Hadoop or Spark, is key, and experience with Databricks or orchestration tools like Airflow would be a plus.

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How does Massive Entertainment support its MLOps Engineers in their work?

Massive Entertainment fosters a collaborative environment where MLOps Engineers work closely with Data Scientists, Data Engineers, and IT Support. The studio encourages a culture of continuous learning and improvement, offering opportunities to stay updated with industry trends and technologies in machine learning and data processing.

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What kind of projects will an MLOps Engineer at Massive Entertainment be involved in?

As an MLOps Engineer at Massive Entertainment, you will support projects that enhance gaming experiences, such as developing and maintaining solutions for game intelligence. You'll focus on industrializing advanced data processing prototypes and creating monitoring tools for ML model performance and data quality, ultimately contributing to the success of beloved titles.

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Common Interview Questions for MLops Engineer [Game Intelligence]
Can you explain your experience with data pipeline design as an MLOps Engineer?

To effectively answer this question, describe specific examples of data pipelines you have designed, focusing on the technologies used and the outcomes achieved. Emphasize your understanding of the challenges in data handling and how you overcame them to ensure seamless processing.

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What machine learning frameworks are you most comfortable with?

Discuss the machine learning frameworks you are experienced with, providing insights into how you've applied them in previous projects. Mention specific use cases and results to give depth to your experience, while also showing your eagerness to learn new technologies.

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How do you ensure high data quality in your MLOps processes?

Explain the strategies you employ to monitor and ensure data quality, such as implementing automated checks and using robust validation techniques. Share specific tools or practices you’ve adopted to maintain high standards in data processing.

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Can you describe a complex problem you've solved in previous MLOps work?

Detail a specific complexity you encountered, your approach to diagnosing the issue, and the steps taken to resolve it. This showcases your critical thinking and problem-solving abilities, which are essential qualities for an MLOps Engineer.

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What role does communication play in your work as an MLOps Engineer?

Highlight the importance of clear communication in collaborating with cross-functional teams like Data Scientists and Game Analysts. Mention how you document your processes and findings to facilitate understanding among stakeholders, ensuring smooth workflows.

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How do you stay updated with the latest trends in machine learning?

Share your methods for staying current, such as attending workshops, reading research papers, or participating in online communities. This demonstrates your commitment to continual learning and adaptation in a rapidly evolving field like machine learning.

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What experience do you have with cloud services and distributed architectures?

Discuss specific cloud services you've used in MLOps roles, detailing how you leveraged them for scalability and efficiency. Explain your familiarity with distributed architectures and how they contribute to effective data processing.

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How would you approach optimizing an existing machine learning model?

Describe a systematic approach to model optimization. Talk about evaluating performance metrics, analyzing feature importance, and experimenting with hyperparameter tuning. Providing concrete examples will strengthen your response.

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What tools do you use for ETL processes and why?

Discuss the ETL tools you favor, highlighting their strengths and any specific use cases where they proved beneficial. This showcases your technical expertise and ability to make informed choices regarding tools for data processing.

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How do you prioritize tasks in a fast-paced environment?

Explain your method for task prioritization, discussing techniques like using project management frameworks or prioritizing based on stakeholder need and project timelines. This reflects your ability to manage multiple responsibilities efficiently.

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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
January 10, 2025

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