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Frost & Sullivan is inviting postgraduate students, graduates, and early-career professionals to join our global teams across AI, data, and advisory functions. Intern roles support MetaBrain with applied AI, quantitative models, and trustworthy engineering to turn research into reusable services.
Engineers will work across engineering and data science teams to test controls that ensure trustworthy AI. Stipend is paid for six months, with possible extension based on performance and academic
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.
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.
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.
Engineer and test the controls that make AI‑assisted research and advisory reliable, traceable and appropriately restricted. Work across engineering, data science and domain teams so trustworthy behaviour is evidenced in the system, not only described in policy.
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.
Master's/PhD study or qualification in AI, computer science, data science, cybersecurity or a closely related field with substantive AI training. Practical Python, software testing and basic understanding of authentication, authorization and data handling. An example of a project or research in trustworthy AI, model evaluation, privacy, security, fairness, robustness or explainability.
Preferred: AI assurance frameworks, automated testing, threat modelling, privacy engineering, policy-as-code, data lineage, monitoring or regulated enterprise workflows. Research-integrity or advisory exposure is valuable; a policy-only background without implementation evidence is insufficient for the Engineer role.