AI Research Scientist

• Engage in relevant research and development (R&D) of AI systems, models, and advanced machine learning algorithms that augment physics-driven modeling and simulation systems
• Explore and implement AI-powered simulation tooling in support of AI workflows through reinforcement learning, multi-agent systems, and hybrid modeling approaches
• Collaborate with research, engineering, and product teams to build AI-powered solutions that meet mission-critical modeling and decision-support needs
• Engage in and support the drafting and review of conference and journal articles and presentations, sharing advances with both internal stakeholders and the wider research community.
• Contribute content to technical invention disclosures, including associated narrative, graphics, and engagements in support of patent development
• Perform additional responsibilities (no more than 10% of duties) in support of the company’s technology and product development initiatives.

AI Research Scientist, Applied AI

• Research and design Agent execution framework, providing standardized runtime environment for intelligent agents
• Implement tool call orchestration mechanism, supporting unified abstraction for function calling, API integration, and external system interaction
• Build execution sandbox environment to ensure safety and controllability of Agent operations
• Design task decomposition and planning engine, supporting automatic breakdown of complex goals and execution path optimization
• Implement execution state tracking and anomaly recovery mechanisms to ensure reliability of long-running tasks
• Design hierarchical memory architecture, covering storage and retrieval mechanisms for working memory, short-term memory, and long-term memory
• Research memory compression and summarization techniques, enabling efficient storage of massive interaction history while preserving key information
• Build context-aware memory system, supporting multi-dimensional memory association based on time, task, and user
• Develop memory retrieval augmentation mechanisms, achieving deep integration of RAG and Agent memory
• Explore memory forgetting and update strategies, balancing memory capacity with information timeliness
• Research multi-Agent system architecture, design communication protocols and collaboration mechanisms between Agents
• Implement role specialization and task allocation algorithms, supporting orchestration of expert Agents, coordinator Agents, executor Agents, and other roles
• Build consensus achievement and conflict resolution mechanisms to handle decision disagreements among multiple Agents
• Design Agent social behavior norms, simulating communication, negotiation, and feedback patterns in human team collaboration
• Explore emergent behavior and collective intelligence, researching self-organization and adaptive capabilities in multi-Agent systems
• Design Agent evaluation and benchmarking system, establishing quantitative capability metrics
• Build Agent behavior interpretability framework, supporting decision process tracing and attribution analysis
• Research Agent safety alignment mechanisms to prevent risks such as unauthorized operations, harmful outputs, and goal drift
• Track cutting-edge Agentic AI research and translate academic achievements into engineering practice.

AI Researcher Intern

• Research, design, develop, and test Pearson’s bedrock learner model to power the next generation of pan-business unit AI-driven learning products
• Partner with Product, Engineering, and Design teams to define and implement AI strategies across higher education courseware and direct to consumer learning products
• Design, develop, and maintain a scalable AI data and delivery architecture to deliver real-time personalized features including proficiency estimates and recommendations upon which we build the future of learning from Pearson
• Using this architecture, develop the customer-facing AI capabilities with which Pearson can re-invent our courseware business for the AI age
• Test and iterate quickly without sacrificing quality (0 to go-to-market in <6months)
• Translate product opportunities into clear data requirements
• Build prototypes, articles, and presentations to educate the organization (including senior executives) on the latest AI innovations and how we will turn them into business growth
• Publish and patent new math, data, and AI inventions
• Collaborate with Data Engineering to ensure clean, reliable data pipelines and seamless front-end delivery
• Evangelize a data-informed culture across Product and Engineering teams through education, enablement, and scalable tooling
• Monitor data quality and tracking integrity, proactively identifying and resolving gaps or anomalies
• Be undaunted by urgency and ambiguity and be persistent in defining requirements and creative in designing solutions.
• Wrangle and clean data as needed.
• Support fellow data analysts, data scientists, and engineers to solve data problems, solve customer and product problems with data, govern quality data, and connect data problems with technical solutions.

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AI Research Scientist, Applied AI

AI Researcher Intern

Lead Specialist, AI Scientist