ML Engineer (RecSys)

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:

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.
• Proficiency in programming languages such as Python and frameworks like TensorFlow or PyTorch.
• Experience with data manipulation and analysis using Pandas, NumPy, and similar tools.
• Strong understanding of machine learning algorithms, particularly collaborative filtering, matrix factorization, and neural networks.
• Experience with database technologies such as MySQL, PostgreSQL, or MongoDB.
• Familiarity with cloud services (e.g., AWS, Google Cloud, Azure) and containerization (e.g., Docker).
• Strong problem-solving skills and the ability to work independently and as part of a team.
• Excellent communication skills and the ability to collaborate with cross-functional teams.
• Experience with real-time data processing frameworks such as Apache Kafka is a plus.

Benefits:

• Competitive salary and equity options.
• Opportunity to work on a cutting-edge social platform and make a significant impact.
• Collaborative and dynamic work environment.
  
  
  Contact (tg): @alena_chernykhh