Member of Technical Staff (Machine Learning Research Engineer)

About the job

Responsibilities

• Advance search quality through models, data, tools, or other leverage.
• Architect and build core components of the search platform and model stack.
• Design, train, and optimize large-scale deep learning models using PyTorch, distributed training, and hardware acceleration, focusing on retrieval and ranking.
• Conduct advanced research in representation learning, including contrastive, multilingual, and multimodal modeling for search and retrieval.
• Deploy models, from boosting algorithms to LLMs, scalably and performantly.
• Build and optimize RAG pipelines for grounding and answer generation.
• Collaborate with Data, AI, Infrastructure, and Product teams for fast, high-quality delivery.

Requirements

• Deep understanding of search and retrieval systems, including quality evaluation principles and metrics.
• Proven track record with large-scale search or recommender systems.
• Strong proficiency with PyTorch, including distributed training techniques and performance optimization for large models.
• Expertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applications.
• Strong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR).
• Self-driven with a strong sense of ownership and execution.
• Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas.