Recommendation Systems Engineer

Main mission

Builds engines that personalize content, products, and feeds.

5 key responsibilities

• Design personalization algorithms: collaborative filtering, ranking, embeddings.
• Build real-time pipelines for features and scoring.
• Measure impact through A/B tests: engagement, conversion, diversity.
• Manage cold start, popularity bias, and filter bubbles.
• Align recommendations with long-term value, not just clicks.

Key skills

Ranking systems, embeddings, A/B testing, streaming, engagement metrics.

What's expected

Recommendations that create lasting value for users and businesses, measured rigorously.

Career paths

Lead ML Product, Personalization Architect, AI Product Manager.