Lead Machine Learning Engineer (Male/Female/Non-Binary)

Company Description

Ubisoft’s 20,000 team members, working across more than 40 locations around the world, are committed to a common mission of enriching players' lives with unique and memorable gaming experiences. Their dedication and talent has 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 thrilled by the idea of solving game-changing challenges, utilizing cutting-edge technologies, and pushing the limits of entertainment, we invite you to join our journey and help us create the unknown.

Job Description

Ubisoft is inherently data-driven. We use data and algorithms from the core of our games to our marketing activities.

As part of the Ubisoft Data Office, the role of the Consumer Data Domain is to leverage data to enhance the consumer experience, engage them throughout their journey, while ensuring they feel safe and cared for.

Your role:

Reporting to the Director of the Consumer Domain, your role will be to build scalable machine learning systems to maintain the trust and safety of our users. Our mantra is to not stop at the prototyping phase, instilling a blend of research and engineering cycles with the aim to deploy production-grade products.

In this context, we're seeking a Lead Machine Learning Engineer with prior practical experience, ideally in the field of anomaly/ fraud detection.

Missions:

Straddling between individual contribution and leadership, the typical missions for this position will be to:

• Take ownership of the projects you build and drive them forward.
• Evaluate new machine learning methods and models, implementing them from scratch if necessary.
• Write, optimize, and generate high-quality code that can operate at scale, adhering to modern best practices (MLOps).
• In collaboration with data and software engineers, deploy models or prediction pipelines to production in our internal or public cloud infrastructures.
• Lead and manage a team of 2 ML engineers focusing on detection subjects.
• Develop and implement an all-inclusive strategy to improve the security of our users and reduce fraud.

Qualifications

Whether you are a software engineer with a passion for Machine Learning, or a research individual who loves engineering, the key attributes needed for this role are:

• Proficient Python programming skills.
• Familiarity with Machine learning & Deep Learning frameworks.
• Experience with anomaly detection, unsupervised, and/or semi-supervised learning is a strong advantage.
• A "try hard, fail fast" mindset: research is rapidly changing, and no one can be familiar with all the subfields of Machine Learning in detail. However, we are never afraid to try our hand at a new research paper or open-source repository with cluttered code, and you shouldn't be either.
• Experience deploying models into production.
• Strong communication skills (proficiency in English required).
• Experience managing a team.

Additional Information

Ubisoft’s Perks

💰 Profit Sharing, annual company saving plan. 25 paid days off + 12 additional paid days off. 50% of your Navigo pass is covered by the company, lunch vouchers (9€/day), healthcare for you and your family, and a plethora of additional perks from Ubisoft.

📍 Our brand-new office is situated in Saint-Mandé, (Metro line 1, Saint-Mandé station). There is a gym in the building. Flexibility to work remotely

Additional information

Skills and competencies present in different forms and can be based on varying experiences; that's why we strongly encourage you to apply, even if you don't meet all the requirements listed above.

At Ubisoft, you can come as you are. We welcome diversity in all its forms. We are committed to fostering a work environment that is inclusive and respectful of all differences.

Check out  to assist you with your application, and learn about our actions to promote more diversity and inclusion.