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Metro location and early-career role but niche socio-technical skills and academic focus limit applicant density.
Social science research skills transfer, but focus on language technologies and rural contexts raises domain specificity.
Emphasis on degree status and research skills but no rigid years or certifications required.
Apply social science research methods to evaluate AI/ML language technologies used by underserved Indian communities.
Develop AI evaluation and testing methodologies with a focus on socio-technical impacts in rural and low-resource contexts.
Collaborate closely with the Evaluations and Tech teams to understand and improve AI system build and evaluation processes.
Pursuing or recently completed undergraduate or master's in social science disciplines (e.g., Sociology, Anthropology, Economics, Political Science).
Conceptual understanding of AI/ML systems demonstrated via coursework, self-learning, or projects; coding skills not required.
Research training in qualitative, quantitative, or mixed methods expected; experience with focus group discussions and field visits preferred.
Work Experience Required: Not explicitly mentioned in the JD.
Has interdisciplinary interests bridging social sciences and AI/ML evaluation particularly in Indian linguistic and rural contexts.
Comfortable working in ambiguous, early-stage research settings with a socio-technical systems perspective.
Possesses multilingual proficiency in Indian languages or background in computational social science is a plus.