TL;DR

Research Intern (GenAI): Supporting innovative research in Generative AI, multilingual technologies, and agentic AI systems with an accent on dataset development and model evaluation. Focus on prompt engineering, red teaming, and analyzing crosslinguistic differences in AI performance.

Location: Remote from Australia, with offices in Sydney (Chatswood).

Company

%hirify_global% is a leader in AI training data, specializing in human-generated data to train, fine-tune, and evaluate models for over 30 years.

What you will do

Conduct literature reviews on topics such as adversarial prompting, multilingual evaluation, and agentic AI.
Assist in dataset curation, annotation, and quality assurance for speech, text, and multimodal data.
Support model evaluation experiments, including prompt engineering and red teaming.
Develop scripts and tools for data analysis, visualization, and automation.
Contribute to internal documentation, research reports, and thought leadership content.
Participate in team meetings and cross-functional collaborations.

Requirements

Postgraduate students in Linguistics, Computer Science, AI, or Data Science preferred; strong final-year and recent undergraduate candidates will also be considered.
Familiarity with programming languages such as Python or R.
Experience with data annotation, model evaluation, or prompt engineering.
Understanding of multilingual NLP, speech technologies, or agentic AI systems.
Strong written communication skills, especially for summarizing research and drafting technical content.
Ability to work independently and collaboratively in a remote research environment.
Must be based in Australia.

Culture & Benefits

Hands-on experience in applied AI research with real-world impact.
Mentorship from experienced researchers and exposure to industry workflows.
Opportunities to contribute to publications, datasets, and thought leadership.
A collaborative and inclusive research environment.

Hiring process

AI tools may be used to support parts of the hiring process, such as reviewing applications or assessing responses.
Final hiring decisions are ultimately made by humans.