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Lead Specialist – AI Scientist

  • On-site
    • Durham, North Carolina, United States
    • East Durham, North Carolina, United States
    +1 more
  • Information Technology

Lead AI Scientist | 8–10 yrs | Python, AI/ML, GenAI & AI Agents | HR AI & Digital Transformation | Model Training/Fine-Tuning | Durham, NC | 100% Onsite | 6-Month Contract

Job description

Role Overview

The AI Scientist will help define the technical direction for AI model training, adaptation, and AI Agent development, with a strong focus on transforming HR processes through intelligent AI solutions.

This is a hands-on Scientist and Builder role. The ideal candidate has experience training and adapting models—not simply consuming or calling existing AI models and APIs.

Key Responsibilities

  • Define and drive the technical strategy for AI model training, adaptation, and AI Agents within the AgentOps team.

  • Design, build, train, fine-tune, and evaluate AI/ML models.

  • Develop AI Agents and intelligent automation solutions for HR and enterprise use cases.

  • Support digital transformation initiatives through AI-driven solutions.

  • Build scalable AI services and applications using Python and modern web frameworks.

  • Establish technical standards, architecture patterns, and best practices for AI development.

  • Evaluate new AI/ML technologies, models, frameworks, and agentic approaches.

  • Collaborate with HR, product, engineering, and technology teams to identify opportunities for AI transformation.

  • Translate AI research and emerging technologies into practical, production-ready solutions.

  • Provide technical leadership and mentorship across AI/ML initiatives.

  • Drive innovation within the AgentOps organization and help shape Pearson's AI strategy.

Preferred Technical Background

AI/ML:
Machine Learning • Generative AI • LLMs • AI Agents • Model Training • Fine-Tuning • Model Adaptation • Model Evaluation

Programming & Development:
Python • FastAPI • Flask • Django • REST APIs • AI/ML Application Development

AI Transformation:
Digital Transformation • Enterprise AI • HR AI • HR Automation • Intelligent Agents • Agentic AI

Leadership:
Technical Strategy • Architecture • Standards & Best Practices • Technical Leadership • Cross-functional Collaboratio

Job requirements

Ideal Candidate

The ideal candidate is a hands-on AI Scientist / AI Engineer / Applied Scientist with 8–10 years of experience who can both build AI systems and provide technical leadership. The candidate should have demonstrated experience training or adapting models, building AI-powered applications, and applying AI/Agentic technologies to real-world enterprise problems. Experience in HR AI Agents, digital transformation, Python, and Python web frameworks is particularly valuable.

Required Skills & Qualifications

  • 8–10 years of experience in AI/ML, Data Science, Machine Learning Engineering, or a closely related field.

  • Strong hands-on experience training, fine-tuning, adapting, and evaluating AI/ML models.

  • Strong Python programming experience.

  • Experience with Python web frameworks such as FastAPI, Flask, or Django.

  • Experience building and deploying AI-powered applications and services.

  • Experience with Generative AI, LLMs, and AI Agents.

  • Experience designing or developing AI Agents / Agentic AI solutions.

  • Experience applying AI to HR / Human Resources processes or other enterprise business functions.

  • Strong understanding of Digital Transformation and using AI to automate and improve business processes.

  • Experience developing HR AI Agents or intelligent assistants for HR-related use cases is highly desirable.

  • Strong technical leadership skills with the ability to establish technical direction, standards, and best practices.

  • Experience evaluating emerging AI technologies and translating them into scalable enterprise solutions.

  • Strong understanding of model evaluation, optimization, and performance improvement.

  • Ability to work closely with engineering, product, HR, and technology stakeholders.

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