Principal Scientist, Language & Personal Intelligence

Samsung Research America • Mountain View, CA

5d • Onsite

About The Position

The Language & Personal Intelligence (LPI) Lab at Samsung Research America focuses on advancing next-generation AI systems that understand, reason, remember, and adapt to users over time. Our mission is to build deeply personalized, context-aware, and agentic intelligence that operates efficiently across devices and ecosystems, combining foundational research with real-world impact at global scale. Position Summary: We are seeking a research leader to drive innovation in Language & Personal Intelligence , with a strong emphasis on agentic reasoning, adaptive memory, and lifelong learning systems . This role will lead research efforts at the intersection of language models, planning agents, memory architectures, and reinforcement learning—enabling AI systems that reason, plan, and evolve with individual users over long time horizons. Opportunity to shape foundational research in adaptive, agentic AI with global impact Collaboration with world-class researchers across language, cognition, and systems

Requirements

• PhD in AI, Machine Learning, NLP, Cognitive Computing, Knowledge representation and reasoning or related field , or equivalent combination of education, training, and experience
• 14+ years of research experience in the fields of AI/NLP/ML
• Strong publication record in areas such as language models, agentic systems, reinforcement learning, memory or adaptive AI
• Deep expertise in modern ML frameworks (PyTorch, TensorFlow, JAX)
• Proven experience with LLMs , retrieval-based systems , or knowledge-augmented NLP
• Strong understanding of: Agent-based architectures Multi-step reasoning and planning Personalization and user modeling
• Excellent communication skills and ability to influence both research and product strategy
• Self-evolving and long-term memory construction
• Retrieval-Augmented Generation (RAG) and related AI architectures
• Agentic reasoning and planning systems
• Reinforcement learning methods for reasoning, adaptation, and personalization

Nice To Haves

• Research or hands-on experience in: Continual / lifelong learning Nested learning and hierarchical learning frameworks Hopfield networks, energy-based models, or associative memory systems Progressive planning and hierarchical RL Personalized agents and user-centric decision-making
• Experience bridging theory and applied systems , including deployment-aware research
• Contributions to open-source projects or publicly released research artifacts

Responsibilities

• Define and lead research agendas in agentic language intelligence , adaptive personalization, and long-term user modeling
• Research, design and develop self-evolving memory systems enabling persistent, personalized, and contextual AI behavior
• Advance Retrieval-Augmented Generation (RAG) and hybrid reasoning systems that combine memory, retrieval, planning, and language understanding
• Lead research on agentic reasoning , including: Reinforcement Learning (RL, RLHF, offline/online RL) Progressive and hierarchical planning Personalized planning and decision-making Multi-step reasoning and goal-directed agents
• Explore continual and lifelong learning approaches that allow models to adapt
• Investigate and prototype learning frameworks and associative memory like architectures for personalized reasoning and recall
• Collaborate closely with engineering and product teams to transition research into scalable, production-ready systems
• Publish at top conferences (NeurIPS, ICML, ICLR, ACL, EMNLP) and contribute to patents and internal innovation initiatives
• Mentor researchers and shape the scientific direction of the Language & Personal Intelligence Lab

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees