AI Transformation Lead Scientist

Prophecy Technologies Corp; Durham (NC); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Pearson is seeking a Lead Specialist, AI Scientist within the Office of the Chief Technology Officer (OCTO). The role drives AI transformation across the AgentOps team, setting the technical direction for model training and adaptation.

It combines hands-on model development with leadership, mentoring, and collaboration with business stakeholders. The successful candidate will train models, define standards, and mentor others while ensuring robust experimentation and practical deployments that

Qualifications

• Proficiency in Python and deep learning frameworks is required.
• Hands-on experience with model training, fine-tuning and deployment.
• Experience with AI transformation initiatives in HR is preferred.
• Ability to mentor and lead technical teams.
• Strong collaboration and communication with non-technical stakeholders.

Responsibilities

• Set the technical direction for model training and adaptation within the AgentOps team.
• Act as a hands‑on scientist and builder, actively training models.
• Provide technical leadership and establish standards for the team.
• Conduct pragmatic experiments and assess readiness for deployment.
• Mentor colleagues and enhance the team's capabilities.
• Translate model behavior into actionable insights for business stakeholders.
• Establish technical standards and guide engineers/scientists.

Skills

Python

Deep Learning

Distributed Training

Cloud Platforms

Model Fine-Tuning

AI Transformation

AI Agents

Communication Skills

Mentoring

Experiment Design

Job description

Pearson is seeking a Lead Specialist, AI Scientist within the Office of the Chief Technology Officer (OCTO). The role drives AI transformation across the AgentOps team, setting the technical direction for model training and adaptation.

It combines hands-on model development with leadership, mentoring, and collaboration with business stakeholders. The successful candidate will train models, define standards, and mentor others while ensuring robust experimentation and practical deployments that