Senior Machine Learning Engineer

Details

Work Location Type:
Hybrid
Office:
London
Type of Employment:
Full Time Permanent
Reference Number:
PRO0311

About Us

At FDJ UNITED, we don't just follow the game, we reinvent it.

FDJ UNITED is one of Europe’s leading betting and gaming operators, with a vast portfolio of iconic brands and a reputation for technological excellence. With more than 5,000 employees and a presence in around fifteen regulated markets, the Group offers a diversified, responsible range of games, both under exclusive rights and open to competition. We set new standards, proving that entertainment and safety can go hand in hand. Here, you’ll work alongside a team of passionate individuals dedicated to delivering the best and safest entertaining experiences for our customers every day.

We’re looking for bold people who are eager to succeed and ready to level-up the game. If you thrive on innovation, embrace challenges, and want to make a real impact at all levels, FDJ UNITED is your playing field.

Join us in shaping the future of gaming. Are you ready to LEVEL-UP THE GAME?

The role

We are now at the next stage of our journey, building our capability for developing end-to-end machine learning data products, from research conducted by our Data Scientists through to production applications built by our Machine Learning Engineers.

Our Machine Learning Engineers align with and work closely with Data Scientists in cross-functional product teams and are jointly responsible for the development of high-quality data products. We are currently focusing on areas including personalisation and relevancy, and product risk management.

Additionally, we are building the core toolset and capability required for our product teams to scale efficiently and iterate rapidly. This includes our Model as a Service deployment platform, developing a feature store for use in both research and production contexts, and building the tooling we need to monitor and test our products.

Part of this role, you will ensure that you adhere to the Governance, Risk & Compliance (GRC) obligations for your role. Identify and raise any non-compliance incidents promptly to your line manager.

Challenge processes, policies and projects that will negatively impact compliance within the Group. Complete all mandatory compliance training assigned to you.

Reach out to the Compliance Teams if unsure of any of your compliance obligations or the requirements are unclear.

About you

We think that to be successful in this role you will be able to demonstrate many of the following attributes:

3-5 years relevant commercial experience delivering a portfolio of ML products
Solid understanding of the machine learning model lifecycle and operations
Experience deploying models as batch, streams, and as services (MLOps)
Strong Scala/Java skills
Strong Python skills
Experience using Spark and other streaming technologies (e.g. Kafka Streams)
Experience in cloud computing, ideally AWS.
Interest in exploring new technologies e.g. LLMs, GenAI
Excellent interpersonal skills: able to collaborate, explain complex topics and contribute to the success of cross-functional DS/MLE product teams.
Ability to deal with and account for uncertainty, with the flexibility to learn by iteration. Proactive.

In addition, it would be an advantage if you also have:

A knowledge of enterprise data concepts, including Data Mesh.
AWS certification.
An interest in mentoring and coaching more junior team members.

Our Way Of Working

Our world is hybrid.

A career is not a sprint. It’s a marathon. One of the perks of joining us is that we value you as a person first. Our hybrid world allows you to focus on your goals and responsibilities and lets you self-organise to improve your deliveries and get the work done in your own way.

Application Process

We believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics as the age, gender, origin, religion, sexual orientation, neurodiversity or disability.