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.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.