Remote: Lead AI Scientist for Learner Intelligence & Graphs

Pearson; Raleigh (NC); Remoto; USD 150.000 - 190.000; Tempo pieno

Descrizione del lavoro

Pearson is seeking a strategic Lead Specialist- AI Scientist to design, build, deploy, and scale production AI/ML capabilities powering learner intelligence, knowledge graphs, recommendations, and personalized learning experiences.

The role spans AI research, data science, software engineering, and product delivery, leading end-to-end AI delivery, MLOps, and governance while mentoring engineers and collaborating with product teams to deliver measurable learner and business outcomes.

Competenze

• Proficient in Python for building production-grade ML solutions.
• Experience with MLOps, deployment, and monitoring.
• Strong collaboration with product, engineering, and data science teams.
• Solid understanding of AI safety, governance, and scalable architectures.

Mansioni

• Lead design, development, deployment, and operation of production AI capabilities.
• Design GenAI, LLM, RAG, and agentic AI solutions with measurable impact.
• Build reusable AI platform components, services, APIs, and workflows.
• Own end-to-end AI delivery lifecycle from prototyping to production.
• Establish scalable MLOps and AIOps practices for reliability and cost.
• Collaborate with Product, Engineering, Learning Science, and Data Science teams.

Conoscenze

Python proficiency

MLOps

Cloud-native development

Cross-functional collaboration

Production operations

Formazione

Bachelor's degree in Computer Science or related field

Master's or PhD in CS/AI (preferred)

Strumenti

AWS

Kubernetes

Terraform

CI/CD pipelines

Descrizione del lavoro

Pearson is seeking a strategic Lead Specialist- AI Scientist to design, build, deploy, and scale production AI/ML capabilities powering learner intelligence, knowledge graphs, recommendations, and personalized learning experiences.

The role spans AI research, data science, software engineering, and product delivery, leading end-to-end AI delivery, MLOps, and governance while mentoring engineers and collaborating with product teams to deliver measurable learner and business outcomes.