Machine Learning Engineer
hace 5 días
About Fever España
Fever España is a leading global live-entertainment discovery tech platform with a clear mission: to democratize access to culture and entertainment. Our proprietary technology inspires a global community of over 125M people through personalized and curated experiences in their local city, while empowering entertainment and event creators to reach new audiences and enhance their experience.
The Role
We are seeking a highly skilled Machine Learning Engineer to join our engineering team. As a Machine Learning Engineer, you will be responsible for creating and maintaining an end-to-end machine learning pipeline. You will work closely with data scientists and data engineers to help set up experiments and design models. Your goal will be to bring models to production that have a direct impact on the end-user experience.
Key Responsibilities
- Deploy trusted models that power Fever's decision-making
- Design, build, and support modern and scalable machine learning infrastructure
- 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 analysts and data scientists more efficient
What You'll Achieve
- Be fully integrated into the team within the first month
- Get a deep dive into the current data science efforts and meet the different departments at Fever
- Get familiar with Fever's tech stack and frameworks
- Attend some of the Fever Original's experiences
- Deploy models to production that have a direct impact on user experience
- Identify gaps in our platforms and processes and be a champion for continuous improvement
- Mentor other new joiners to the team
Requirements
We are looking for a highly skilled Machine Learning Engineer with experience in creating and maintaining end-to-end machine learning pipelines. You should have a strong background in machine learning, data science, and software engineering. You should also be able to work closely with data scientists and data engineers to help set up experiments and design models.
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