Member of Technical Staff Machine Learning Research Engineer

You will advance search quality by building core search-platform and model-stack components. You will design, train, optimize, and deploy large-scale retrieval and ranking models; research representation learning; build RAG pipelines; and work with Data, AI, Infrastructure, and Product teams to deliver high-quality systems quickly.

Responsibilities

• Improve search quality through models, data, tools, and other approaches
• Architect and build core search-platform and model-stack components
• Design, train, and optimize large-scale deep-learning models for retrieval and ranking
• Conduct research in representation learning, contrastive learning, multilingual modeling, and multimodal modeling
• Deploy scalable, performant models ranging from boosting algorithms to LLMs
• Build and optimize RAG pipelines for grounding and answer generation
• Collaborate with Data, AI, Infrastructure, and Product teams to deliver quickly and with high quality

Requirements

• Deep understanding of search and retrieval systems, including quality evaluation principles and metrics
• Proven track record with large-scale search or recommender systems
• Proficiency with PyTorch, distributed training techniques, and large-model performance optimization
• Expertise in representation learning, contrastive learning, and embedding-space alignment for multilingual and multimodal applications
• Strong publication record in AI or ML conferences or workshops
• Minimum of 3 years working on search, recommender systems, or closely related research areas