Lead Specialist AI 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, a global leader in learning, is seeking a Lead Specialist, AI Scientist for its Office of Chief Technology Officer (OCTO). This role is pivotal in driving the future of AI Transformation within Pearson's AgentOps team, focusing on setting the technical direction for model training and adaptation. The successful candidate will inspire innovation and empower learning through advanced AI solutions.

Key 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 rather than just utilizing them.
• Provide technical leadership, setting standards through credibility and expertise.
• Conduct pragmatic experimentation, discerning when results are robust enough for deployment.
• Mentor colleagues, measurably enhancing the capabilities of the team.
• Collaborate effectively, translating complex model behavior into actionable decisions for business stakeholders.
• Establish technical standards and mentor other engineers or scientists.

Required Skills:

• Proficiency in Python Web Frameworks.
• Experience with AI Transformation for HR.
• Expertise in AI Agents.
• Demonstrated hands‑on experience in post‑training and fine‑tuning foundation models, including supervised fine‑tuning, parameter‑efficient methods (e.g., LoRA, QLoRA), preference optimization (e.g., RLHF, DPO), or distillation.
• Strong Python and deep learning framework skills, encompassing distributed or multi‑GPU training.
• Rigor in data curation, experiment design, and evaluation, with the ability to provide evidence of model improvement.
• Depth in one or more AI/ML areas, coupled with the breadth to make architectural and tooling decisions for a team.
• Experience with public cloud platforms and their AI‑related services, including taking models into production.
• Clear communication skills for senior and non‑technical audiences, covering trade‑offs, cost, and risk.
• Understanding of AI/ML applications in educational content, assessment, and personalized learning.

Qualifications:

• 8-10 years of relevant experience.
• A track record of setting technical standards and mentoring other engineers or scientists.