Note: The job is a remote job and is open to candidates in USA. Cambium Learning Group is an educational technology company that develops personalized SaaS resources and instructional products to support students and teachers. The Software Engineer Intern will contribute to AI-powered educational assessment systems by developing generative AI features, supporting AI agent workflows, integrating AI capabilities, and evaluating system quality, safety, and performance.
Responsibilities
- Assisting in the development of AI‑powered features using Large Language Models (LLMs)
- Supporting AI agent workflows, including prompt design, tool integration, and basic orchestration logic
- Helping integrate generative AI capabilities into educational platforms
- Contributing to evaluation and testing of AI systems for quality, safety, and performance
- Collaborating with engineers, product managers, and researchers on real‑world learning use cases
- Exploring responsible AI practices in a mission‑driven education environment
Skills
- You must reside and work in the US for this internship position
- Currently pursuing a postgraduate degree in Computer Science, Data Science, Software Engineering, AI/ML, or a related field
- Experience (academic or project‑based) with at least one programming language such as Python, JavaScript/TypeScript, or C#
- Familiarity with web development, APIs, or backend systems
- Interest in Generative AI, LLMs, or intelligent systems
- Strong problem‑solving skills and eagerness to learn
- Ability to collaborate effectively in a team environment
- Coursework or projects involving advanced AI, machine learning, or NLP
- Exposure to cloud platforms (AWS, Azure, or GCP)
- Interest in education technology or applied learning sciences
Benefits
- Remote work arrangement for interns who reside and work in the US
- Hands-on experience contributing to real AI products
- Learning from experienced engineers at the forefront of EdTech
- Practical experience working with modern AI and generative technologies
- Experience with how production-grade AI systems are designed, tested, and deployed
- Learning best practices for building safe, scalable, and user-focused AI features
- Experience collaborating with cross-functional teams on learning science, technology, and user needs
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