About this role
Launch Your Career with Frost & Sullivan
At Frost & Sullivan, we believe that the future belongs to curious minds, innovative thinkers, and problem-solvers who are eager to make an impact. We are inviting applications from postgraduate students, recent graduates, and early-career professionals with up to two years of experience to join our growing global teams across various business, technology, research, consulting, AI, data, and corporate functions.
The Opportunity
Frost & Sullivan is looking for intern roles supporting MetaBrain. The work combines applied AI, business understanding, structured knowledge, quantitative models and trustworthy engineering to transform research and advisory into reusable software-enabled services. Build more than a demonstration. Work with industry researchers, advisors and engineers to turn AI capability into tested decision-intelligence software that enterprises can use.
Role Overview
Show how your technical work supports a business problem. Research, consulting or advisory experience is preferred but not mandatory. Academic projects, thesis and reproducible research implementations are valid evidence; internships do not require prior full-time employment.
Translate a business decision into an AI-enabled solution that can be tested, integrated and operated. Work with Frost domain experts to connect research methods, knowledge structures, data, reasoning workflows and client-facing experiences.
Proposed engagement
Stipend: Yes, paid internship.
Duration: Preferably six months, possibility of an extension up to 12 months based on performance and where academic arrangements and work authorization permits are in place.
Full-time Conversion: Depends on assessed performance, a suitable vacancy and eligibility; it is not guaranteed.
Essential requirements
Currently pursuing or holding a Master's or PhD in AI, machine learning, computer science, data science or a closely related field with substantial AI work. Strong Python, APIs, data structures and software-engineering fundamentals. One demonstrable end-to-end AI prototype or research implementation, with clear individual contribution. Ability to explain how a model supports a business decision.
Preferred: Knowledge graphs, information retrieval, agent workflows, enterprise integration, cloud services, user-experience design or applied business projects. Research or consulting exposure is advantageous, not mandatory; production experience is not required for interns.
Key responsibilities
• Understand the business problem: Join discovery and document the user, decision, alternatives, constraints and success measure. Translate an advisory brief into Input-Process-Output specifications, acceptance tests and a scoped backlog.
• Prototype the architecture: Design structured knowledge representations and retrieval grounded in approved sources. Connect model outputs to deterministic calculations, APIs and tools; implement constrained workflows with clear human-review points.
• Evaluate the whole system: Compare retrieval and orchestration designs; measure factual support, task completion, latency and operating cost. Test failure handling and access boundaries and explain architecture choices to both business and engineering mentors.
• Prepare for reuse: Create configuration schemas, interfaces, automated tests and architecture records. Contribute to advisor Design/Tuning and client Advisory/Simulation experiences; document handover, deployment assumptions and observability.