Own the Visual Gateway: Deliver the features that identify the first thing millions of users see when they open our apps.
Drive Systematic Quality: Improve the reliability and velocity of our experimentation systems, ensuring our visual tests are statistically sound and performant.
Scale Discovery: Build the components that allow us to personalize the 'look and feel' of the platform, not just the content list.
Feature & Component Ownership: Design and implement specific solutions for Multi-Armed Bandit (MAB) systems and visual feature pipelines.
Self-governing Delivery: Own the end-to-end implementation of defined tasks, from data ingestion to production deployment, with moderate autonomy.
System Optimization: Proactively identify and fix bottlenecks in team systems to improve quality, reliability, or engineering velocity.
Collaborative Quality: Participate actively in design and code reviews, providing constructive feedback and ensuring high technical standards within your scope.
Data-Driven Execution: Set up and monitor online experiments (A/B tests and bandit rollouts) to measure the impact of presentation features on user interaction.

3+ years of experience in machine learning engineering or backend software engineering.
Proven Delivery: Experience owning and delivering technical features or components autonomously.
Technical Stack: Proficiency in Python and experience with ML frameworks like PyTorch or TensorFlow.
Data Foundations: Strong skills in SQL and experience with distributed data processing (e.g., Spark or Databricks).
Engineering Rigor: Familiarity with version control, CI/CD, and writing production-grade, maintainable code.
Familiarity with Multi-Armed Bandits or Reinforcement Learning concepts.
Background in Computer Vision or image processing.
Experience in a high-scale streaming or e-commerce environment.
Experience with Cloud Infrastructure, including AWS, GCP, and Azure.

Machine Learning Engineer, Presentation and Visual Optimization

Key skills