Research Scientist - AI Agent Memory Infrastructure - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

What you'll do

• Build and optimize large-scale memory pipelines for ingestion, storage, indexing, retrieval, updating, compression, and forgetting.
• Research memory representation, retrieval and ranking, conflict resolution, summarization, multimodal fusion, and memory lifecycle management.
• Collaborate with model, application, and platform teams to productionize memory capabilities and improve quality, latency, cost, reliability, and safety.

What they ask for

• Completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, Artificial Intelligence, or a related technical discipline.
• Strong experience in distributed systems, databases, information retrieval systems, or AI infrastructure, with system design and production engineering capabilities.
• Proficiency in at least one programming language such as Go, Python, or C++.
• Solid understanding of LLM application technologies, including embeddings, retrieval-augmented generation (RAG), context engineering, retrieval systems, or long-term state management; familiarity with at least one key area of memory systems.

Nice to have

• Experience with agent memory systems, user profiling, recommendation/search feature platforms, or knowledge base systems.
• Contributions to or deep understanding of open-source memory frameworks such as mem0, memOS, or memU; or a strong track record in relevant research or engineering.

Tools

Go, Python, C++, LLMs, RAG, mem0, memOS, memU

AI focus

Research and engineering of AI-agent memory infrastructure, including long-term, conversational, task-oriented, and multimodal memory, and its production integration with LLM-powered applications.