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- Tasks: Develop and operationalise machine learning models to enhance gaming experiences.
- Company: Leading interactive entertainment company in the UK with a focus on innovation.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Why this job: Join a team impacting over 250 million users with cutting-edge AI technology.
- Qualifications: Strong Python skills and experience in delivering ML systems and data pipelines.
- Other info: Be part of a collaborative culture that values pragmatic engineering.
The predicted salary is between 48000 - 72000 £ per year.
A leading interactive entertainment company in the UK is seeking a Principal AI/ML Engineer for their AI Center of Excellence. This hands-on role involves developing and operationalizing machine learning models to enhance gaming experiences for over 250 million users.
Ideal candidates will have:
- Strong Python skills
- A proven track record in delivering ML systems
- Experience in building data pipelines
Join a team that values innovation and pragmatic engineering in a dynamic tech environment.
Principal AI/ML Engineer - Ship Production ML for Games in London employer: King
Contact Detail:
King Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal AI/ML Engineer - Ship Production ML for Games in London
✨Tip Number 1
Network like a pro! Reach out to folks in the gaming and AI/ML space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those related to gaming. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on Python and ML concepts. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our innovative team.
We think you need these skills to ace Principal AI/ML Engineer - Ship Production ML for Games in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python expertise in your application. We want to see how you've used it in past projects, especially in developing ML systems. Don’t hold back on the details!
Demonstrate Your ML Experience: Share specific examples of machine learning models you've developed and operationalised. We love seeing a proven track record, so include metrics or outcomes that showcase your impact.
Talk About Data Pipelines: If you've built data pipelines, let us know! Describe the tools and techniques you used, as this is crucial for the role. We’re keen to understand how you handle data flow in your projects.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at King
✨Know Your Python Inside Out
Since strong Python skills are a must for this role, make sure you brush up on your Python knowledge. Be prepared to discuss your experience with libraries like TensorFlow or PyTorch, and maybe even solve a coding challenge during the interview.
✨Showcase Your ML Success Stories
Have a few solid examples ready that highlight your track record in delivering machine learning systems. Talk about specific projects where you developed and operationalised models, and how they enhanced user experiences. Numbers and outcomes speak volumes!
✨Understand Data Pipelines
Since building data pipelines is part of the job, be ready to discuss your experience in this area. Explain the tools and frameworks you've used, and how you've tackled challenges in data processing. This will show your practical engineering skills.
✨Embrace Innovation and Pragmatism
This company values innovation, so come prepared with ideas on how to push the boundaries in AI/ML for gaming. However, balance that with pragmatic solutions. Discuss how you can innovate while still being realistic about implementation and user impact.