Search/Recommendation ML Engineer

About the Role

We are seeking an experienced Machine Learning Engineer to help advance next-generation search, discovery, and recommendation capabilities across a large-scale digital ecosystem. This role offers the opportunity to work on cutting-edge retrieval, ranking, and AI-driven personalization technologies that serve diverse user journeys and business use cases.

You will collaborate closely with engineers, data scientists, researchers, and product teams to design scalable machine learning solutions that improve content discovery, relevance, and user engagement across multiple markets and languages.

Key Responsibilities

• Design and develop high-performance search and recommendation platforms capable of operating at large scale.
• Build and optimize embedding-based retrieval systems that deliver accurate and efficient content matching.
• Enhance ranking and recall performance through the application of machine learning, natural language processing (NLP), and multimodal AI technologies.
• Research, develop, and deploy multilingual, multitask, and multimodal models to improve search relevance and recommendation quality.
• Partner with product and engineering stakeholders to translate business requirements into machine learning solutions.
• Conduct online and offline experiments, including A/B testing, to evaluate model effectiveness and drive data-informed decisions.
• Own the end-to-end machine learning lifecycle, including feature development, model training, validation, deployment, monitoring, and optimization in production environments.
• Develop reusable machine learning frameworks and foundational technologies that can be leveraged across multiple products and business scenarios.
• Analyze complex datasets and user behavior patterns to identify opportunities for improving discovery, personalization, and engagement.
• Collaborate with cross-functional teams of engineers, researchers, and statisticians to deliver innovative AI-powered capabilities across international markets.

Preferred Qualifications

• Strong experience in machine learning, information retrieval, search relevance, or recommendation systems.
• Hands-on expertise with NLP, large language models (LLMs), embeddings, and semantic search technologies.
• Experience building and maintaining large-scale production machine learning systems.
• Solid understanding of ranking algorithms, retrieval architectures, and recommendation methodologies.
• Familiarity with experimentation frameworks and A/B testing methodologies.
• Proficiency in software engineering best practices and production-quality model deployment.
• Ability to work effectively in a highly collaborative, cross-functional environment.

Areas of Impact

• Search \& Discovery
• Recommendation Systems
• Information Retrieval
• NLP \& Large Language Models
• Multimodal AI
• Personalization \& Ranking
• Machine Learning Platform Development
• Experimentation \& Optimization