Recommendation Systems Engineer

Recommendation Systems Engineers build personalization algorithms that suggest products, content, or connections to users. They work with collaborative filtering, content-based methods, and deep learning to optimize user engagement and satisfaction.

Key Responsibilities: • Design and implement recommendation algorithms • Build real-time personalization systems • Optimize ranking and scoring models • Conduct A/B tests on recommendation strategies • Monitor recommendation quality metrics • Scale recommendation systems to millions of users

Required Skills: Collaborative filtering, matrix factorization, deep learning for recommendations, ranking algorithms, A/B testing, distributed systems, Python, Spark, real-time ML, feature engineering, bandit algorithms

Career Path: Junior recommender engineers work on specific components. Mid-level engineers own recommendation domains. Senior engineers architect platform-wide personalization. Principal engineers set recommendation strategy.

Top Hiring Companies: Netflix, Spotify, Amazon, YouTube, TikTok, Pinterest, Instagram, LinkedIn, Airbnb, DoorDash, Instacart, Shopify, eBay, Etsy