About the company
Appen is a leader in AI enablement for critical tasks such as model improvement, supervision, and evaluation. To do this we leverage our global crowd of over one million skilled contractors, speaking over 180 languages and dialects, representing 130 countries. In addition, we utilize the industry's most advanced AI-assisted data annotation platform to collect and label various types of data like images, text, speech, audio, and video. Our data is crucial for building and continuously improving the world's most innovative artificial intelligence systems and Appen is already trusted by the world's largest technology companies. Now with the explosion of interest in generative AI, Appen is helping leaders in automotive, financial services, retail, healthcare, and governments the confidence to deploy world-class AI products. At Appen, we are purpose driven. Our fundamental role in AI is to ensure all models are helpful, honest, and harmless, so we firmly believe in unlocking the power of AI to build a better world. We have a learn-it-all culture that values perspective, growth, and innovation. We are customer-obsessed, action-oriented, and celebrate winning together. At Appen, we are committed to creating an inclusive and diverse workplace. We are an equal opportunity employer that does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Job Summary
Key Responsibilities
šConduct literature reviews on topics such as adversarial prompting, multilingual evaluation, and agentic AI. šAssist in dataset curation, annotation, and quality assurance for speech, text, and multimodal data. šSupport model evaluation experiments, including prompt engineering and red teaming. šDevelop scripts and tools for data analysis, visualization, and automation. šContribute to internal documentation, research reports, and thought leadership content. šParticipate in team meetings and cross-functional collaborations. šHelp prepare materials for conferences, publications, and workshops.
Preferred Qualifications
šPostgraduate students in Linguistics, or similar disciplines preferred; strong final-year and recent undergraduate candidates in these fields will also be considered. šFamiliarity with programming languages such as Python, R, or similar tools used in data analysis and machine learning. šExperience with data annotation, model evaluation, or prompt engineering. šUnderstanding of multilingual NLP, speech technologies, or agentic AI systems. šStrong written communication skills, especially for summarizing research and drafting technical content. šAbility to work independently and collaboratively in a remote research environment.
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