Machine Learning Engineer - RecommendationsRemote - Americas

Machine Learning Engineer - Recommendations Remote - Americas Great recommendations connect people with products they'll genuinely love. As a Machine Learning Engineer on the Recommendations team, you'll build the personalization technology that powers discovery across Shop surfaces and adjacent recommendation experiences. You'll develop advanced machine learning systems spanning retrieval, ranking, and LLM-based approaches that help millions of buyers discover the right products at the right moment, while supporting millions of merchants in reaching audiences who truly want what they offer. This is an end to end applied ML role: you'll work across data, training, offline evaluation, online experimentation, and streaming/serving infrastructure, with multiple active model families (collaborative filtering / two-tower, LLM-based candidate generation, HSTU /generative approaches, multi-objective rankers) being flighted and iterated in production. Key Responsibilities

• Develop and optimize advanced machine learning models for recommendation systems, including retrieval and multi-objective ranking
• Build and maintain end-to-end ML pipelines, from feature engineering and training through offline evaluation, online experimentation, and production serving
• Scale LLM-based recommendation systems for production, including throughput optimization, QPS management, multi-partition workers, and operational reliability
• Collaborate closely with platform, infrastructure, and product teams to integrate ML solutions into our unified recommendations pipeline
• Research and implement innovative algorithms—including semantic/sequence models, distillation approaches, and relevance grading—to enhance recommendation quality
• Document technical insights, share best practices, and contribute to a strong experimentation culture across engineering teams

Qualifications

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