About Glam:
Glam is an innovative social platform where users can share content they generate using our app, interact through comments and likes, and follow other users. We are on a mission to create a vibrant community of content creators and enthusiasts. Our app includes features such as user profiles with content statistics and real-time notifications for user interactions.
Why Join Us?
- Collaborate with a powerhouse team from top industry players like Lensa, Picsart, Viber, AIRI, and Yandex.
- Gain insights from investors with a track record of successful exits, including the sale of Looksery and AI Factory to Snap for $150M and $166M respectively.
- Be part of a rapidly growing company with $3M ARR and 150,000 happy customers across the US and Europe.
- Dive into innovative backend development strategies in a dynamic and fast-paced startup environment.
Job Description:
We are looking for a talented Machine Learning Engineer specializing in recommendation systems to join our team at Glam. You will be responsible for designing, developing, and maintaining the recommendation algorithms that power our content discovery, user engagement, and personalized experiences on the platform.
Key Responsibilities
- Design and implement scalable recommendation systems to personalize content feeds for users.
- Develop and maintain machine learning models for user interaction prediction, content ranking, and recommendations.
- Work closely with data engineers to build and manage data pipelines for training and deploying models.
- Collaborate with backend developers to integrate recommendation systems into the app’s infrastructure.
- Optimize algorithms for real-time recommendations and high traffic volumes.
- Monitor and troubleshoot model performance, ensuring high accuracy and relevance of recommendations.
- Conduct A/B testing and other experiments to validate the effectiveness of recommendation strategies.
- Stay updated with the latest research and advancements in machine learning and recommendation systems.
Requirements
- Proven experience as a Machine Learning Engineer, particularly in building recommendation systems.