Machine Learning Engineer, Presentation and Visual Optimization

Overview

We are seeking a Machine Learning Engineer to join our Presentation pod. While other teams within AMLG focus on the "recommender(what to show)," our pod owns the "visual gateway." Your mission is to implement and scale the ML systems that optimize how content is displayed to capture user attention.

Key Responsibilities

• 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.

Basic Qualifications

• 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.

Additional Qualifications

• 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.