Lead Specialist - AI Scientist Hudson Manpower Durham, NC Job Details Full-time 18 hours ago Qualifications AI models Performance tuning Performance optimization Automation Team leadership Generative models Scalable systems Digital transformation Collaboration with product development teams Research project technical leadership Machine intelligence Model deployment Applied research Developing large-scale AI models Improving predictive model accuracy Leading team collaboration initiatives Scalability Model training Data science AI-driven automation Model evaluation Generative AI Cross-functional communication Full 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 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.