Hi, we're Fever.
We're excited you are checking out this job offer.
We are the leading global live-entertainment discovery tech platform with a clear mission: to democratize access to culture and entertainment.
How do we achieve our mission?
Fever has developed a proprietary technology that inspires a global community of over 125M people through personalized and curated experiences in their local city whilst empowering entertainment and event creators to reach new audiences and enhance their experience.About the role: You'll help shape how data science is done at Fever.
You'll be responsible for creating and maintaining an end-to-end machine learning pipeline.
You'll work hand in hand with data scientists and data engineers, helping on the experiment setup and model design.
You'll bring to production models that will have a direct impact on the end user experience.
On your first month in Fever: You will be fully integrated into the team.
During this month you will have already participated in onboarding, you'll get a deep dive in the current machine learning efforts and you will have met the different departments at Fever.
You'll get familiar with Fever's tech stack and frameworks.
You will attend some of the Fever Original's experiences like Candlelight.After 3 months in Fever: You'll be able to come up with solutions to new difficult problems and you'll be generating impact and creating new business opportunities.
You'll have responsibilities and ownership over parts of our modeling pipeline or other critical tools.
You will mostly know everybody from the data and engineering communities.On your 6th month in Fever: You'll have deployed to production models that have a direct impact on users and partners.
You'll be able to identify gaps in our platforms and processes and be a champion for continuous improvement.
You'll be mentoring other new joiners to the team.
You will participate in some of the team buildings we organise for your team or the whole engineering team.Key responsibilities:Deploy trusted models that power Fever's decision making.Design, build and support modern and scalable machine learning infrastructure, e.g., Build a reproducible, organized, end-to-end machine learning pipeline.Build model quality and usage monitoring systems.Automate model training.Build tools to make our business processes more efficient.Understand the technical trade-offs of different solutions, implement them, and make them scalable.
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