Research Interns will engage in applied research for Generative AI, assist in dataset development, model evaluation experiments, and contribute to publications and internal documentation.
About Appen
Appen has been a leader in AI training data for over 30 years. We specialise in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Our AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre-training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.
About the Role
Appen is seeking Research Interns to support innovative research in Generative AI, multilingual technologies, and agentic AI systems. As part of our GenAI research team, you’ll contribute to projects that advance safe, inclusive, and effective AI systems across languages and modalities. This internship offers hands-on experience in applied research, dataset development, and model evaluation, with opportunities to contribute to publications and thought leadership.
Key Responsibilities
- 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.
- Help prepare materials for conferences, publications, and workshops.
Preferred Qualifications
- Postgraduate students in Linguistics, Computer Science, AI, Data Science, or similar disciplines preferred; strong final-year and recent undergraduate candidates in these fields will also be considered.
- Familiarity with programming languages such as Python, R, or similar tools used in data analysis and machine learning.
- 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.
Sample Intern Projects
Projects will be tailored to each intern’s background and interests. Examples include:
Multilingual Prompt Engineering & Evaluation
· Design and test prompts across multiple languages.
· Evaluate LLM performance on translation, summarization, and question answering tasks.
· Analyze crosslinguistic differences in prompt effectiveness.
Speech Dataset Analysis & Annotation
· Annotate and analyze multilingual or dialectal speech data.
· Support dataset documentation and quality benchmarking.
· Explore linguistic variation in speech recognition performance.
Red Teaming & Safety Evaluation
· Generate adversarial prompts in multiple languages and modalities.
· Evaluate model responses for safety, bias, and robustness.
· Contribute to internal red teaming frameworks and reporting.
Agentic AI Evaluation & Experimentation
· Explore behaviors of agentic systems in multilingual or multimodal contexts.
· Assist in designing evaluation frameworks for autonomy, safety, and alignment.
· Contribute to internal research on agentic capabilities and risks.
Thought Leadership & Research Communication
· Draft blog posts, white papers, or internal briefs.
· Assist with visualizations and summaries for external publications.
· Support broader research storytelling and knowledge sharing.
What You’ll Gain
· 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.
Top Skills
Data Analysis
Machine Learning
Python
R
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