Senior AI Scientist — Learner Intelligence & Personalization

Pearson; Austin (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Pearson is seeking an AI Platform/ML engineer to lead production AI capabilities across learner intelligence, recommendations, and knowledge graphs. You will shape Generative AI, LLM and agentic solutions, and build scalable AI services that power Pearson products.

You will mentor engineers, collaborate with product, design, and data teams, and drive Responsible AI governance while optimizing cost, latency, and reliability.

Qualifications

• 5+ years of experience building and deploying production AI/ML systems, including cloud-native applications and MLOps practices.
• Strong experience with applied machine learning, Generative AI, LLMs, RAG architectures, recommendation systems, knowledge graphs, or agentic AI solutions.
• Hands-on experience building and deploying AI applications using foundation models and modern AI frameworks.
• Proficiency in Python and modern software engineering practices, including APIs, testing, CI/CD, version control, and production operations.
• Experience designing scalable AI platforms, services, and deployment architectures in AWS or similar cloud environments.
• Experience with containerization, orchestration, infrastructure-as-code, and production‑grade deployment practices.
• Experience evaluating, monitoring, and optimizing AI systems for quality, reliability, safety, latency, scalability, and cost.
• Experience with modern AI technologies such as OpenAI, Anthropic, Bedrock, Azure OpenAI, LangGraph, LangChain, Semantic Kernel, vector databases, or similar platforms.
• Strong collaboration and communication skills with product, engineering, and business stakeholders.

Responsibilities

• Lead design, development, deployment, and operation of production AI capabilities for learner intelligence and personalization.
• Design and deliver Generative AI, LLM, RAG, and agentic AI solutions with measurable business impact.
• Build reusable AI platform capabilities, services, APIs, and workflows that accelerate AI adoption across Pearson products.
• Own the end-to-end AI delivery lifecycle, from experimentation through deployment, monitoring, evaluation, and improvement.
• Establish scalable MLOps and AIOps practices for model training, deployment, observability, governance, reliability, and operational excellence.
• Partner with Product, Engineering, Design, Learning Science, and Data Science teams to identify opportunities and deliver AI capabilities.
• Evaluate emerging AI technologies, foundation models, and architectures balancing quality, safety, scalability, latency, cost.
• Establish best practices for responsible AI, model evaluation, prompt engineering, agent evaluation, and AI governance.
• Mentor engineers and data scientists and elevate AI engineering capabilities.
• Communicate technical strategy, architecture decisions, trade-offs, risks, and outcomes to stakeholders.

Skills

Python

APIs

CI/CD

Production operations

Cloud-native

Collaboration

Communication

OpenAI

Education

Bachelor's degree in Computer Science, Engineering, Data Science, AI/ML, or equivalent practical experience

Tools

Docker

Kubernetes

Terraform

Job description

Pearson is seeking an AI Platform/ML engineer to lead production AI capabilities across learner intelligence, recommendations, and knowledge graphs. You will shape Generative AI, LLM and agentic solutions, and build scalable AI services that power Pearson products.

You will mentor engineers, collaborate with product, design, and data teams, and drive Responsible AI governance while optimizing cost, latency, and reliability.