Lead Specialist, AI Scientist
Job Location:
Hoboken, NJ - USA
Monthly Salary:
Posted:
Application Deadline:
Vacancies:
Department:
Job Summary
Lead Specialist AI Scientist
Location: Hybrid Hoboken
About the Role
We are seeking a strategic and hands-on Lead Specialist- AI Scientist to design build deploy and scale production AI/ML capabilities that power Pearsons learner intelligence knowledge graphs recommendations personalized learning experiences and next-generation AI products.
This role bridges AI research data science software engineering and product delivery. The successful candidate will lead the development of machine learning Generative AI LLM agentic AI and knowledge graph solutions taking them from concept and experimentation through production deployment and continuous improvement. The ideal candidate combines deep technical expertise with a strong execution mindset and a passion for delivering measurable learner and business outcomes.
What Youll Do
- Lead the design development deployment and operation of production AI capabilities supporting learner intelligence personalization recommendations knowledge graphs and AI-powered learning experiences.
- Design and deliver Generative AI LLM retrieval-augmented generation (RAG) and agentic AI solutions that create measurable product and business impact.
- Build reusable AI platform capabilities services APIs and workflows that accelerate AI adoption across Pearson products.
- Own the end-to-end AI delivery lifecycle from experimentation and prototyping through deployment monitoring evaluation and continuous improvement.
- Establish scalable MLOps and AIOps practices for model training deployment observability governance reliability and operational excellence.
- Partner closely with Product Engineering Design Learning Science and Data Science teams to identify opportunities and deliver impactful AI-powered capabilities.
- Evaluate emerging AI technologies foundation models and architectural approaches while balancing quality safety scalability latency and cost.
- Establish best practices for responsible AI model evaluation prompt engineering agent evaluation and AI governance.
- Mentor engineers and data scientists and help elevate AI engineering capabilities across the organization.
- Communicate technical strategy architecture decisions trade-offs risks and outcomes to stakeholders across the business.
Expected Results:
- Production-ready learner intelligence recommendation and knowledge graph capabilities powering personalized learning experiences.
- Enterprise-scale AI services LLM applications and agentic workflows integrated into Pearson products.
- Reusable AI platform components enabling rapid development evaluation deployment and scaling of AI-powered capabilities.
- Reliable secure observable and cost-efficient AI systems operating successfully in production environments.
- Accelerated transition of AI prototypes and research into measurable product and business outcomes.
- Improved learner engagement efficacy productivity and business impact through deployed AI capabilities.
Qualifications
- 5 years of experience building and deploying production AI/ML systems including cloud-native applications and MLOps practices.
- Strong experience with applied machine learning Generative AI LLMs RAG architectures recommendation systems knowledge graphs or agentic AI solutions.
- Hands-on experience building and deploying AI applications using foundation models and modern AI frameworks.
- Proficiency in Python and modern software engineering practices including APIs testing CI/CD version control and production operations.
- Experience designing scalable AI platforms services and deployment architectures in AWS or similar cloud environments.
- Experience with containerization orchestration infrastructure-as-code and production-grade deployment practices.
- Experience evaluating monitoring and optimizing AI systems for quality reliability safety latency scalability and cost.
- Experience with modern AI technologies such as OpenAI Anthropic Bedrock Azure OpenAI LangGraph LangChain Semantic Kernel vector databases or similar platforms.
- Strong collaboration and communication skills with product engineering and business stakeholders.
- Bachelors degree in Computer Science Engineering Data Science AI/ML or equivalent practical experience.
Preferred Qualifications
- Masters degree or PhD in Computer Science Artificial Intelligence Machine Learning Statistics or a related discipline.
- Experience in educational technology personalized learning assessment learning science or related domains.
- Familiarity with psychometrics proficiency modeling Bayesian methods item response theory or educational measurement.
- Experience building AI platforms knowledge graph solutions or agentic systems at enterprise scale.
- Contributions to research patents open-source projects or industry thought leadership.
Apply now and help shape the future of learning.
Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set level of experience and specific location. As required by the California Colorado Hawaii Illinois Maryland Minnesota New Jersey New York State New York City Vermont Washington State and Washington DC laws the pay range for this position is as follows:
The minimum full-time salary range is between $150000 - 190000.
This position is eligible to participate in an annual incentive program and information on benefits offered ishere.
Applications will be accepted through August 30th. This window may be extended depending on business needs.
Required Experience:
IC
About Company
Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gen ... View more
