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Metro location and popular junior AI title increase applicant density, but small nonprofit brand moderates competition.
ML/NLP skills broadly transferable, though civic-tech multilingual focus slightly narrows applicability.
Explicit 1–2 year requirement and specific LLM/NLP skills enforce moderate filters.
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Implement and experiment with prompting strategies, retrieval architectures, and LLM integrations for various projects.
Develop and iterate multilingual conversational AI interfaces and build RAG pipelines for document-heavy datasets.
Assess and improve dataset readiness and build evaluation modules to measure model outputs for hallucination, bias, safety, and privacy in multilingual contexts.
Education: Bachelor’s or Master’s in Computer Science, Engineering, or related field with ML/NLP focus.
1-2 years of experience as AI/ML engineer, data scientist, or software engineer.
Proficiency in Python and working knowledge of LLMs, embeddings, RAG workflows, chatbots, and agentic architectures.
Ability to work autonomously across multiple projects and communicate progress and blockers proactively.
Technically sharp individual comfortable with hands-on AI development and applied research in public sector contexts.
Experience or interest in multilingual and low-resource NLP, preferably Indic languages.
Ability to scope loosely defined ideas into small, testable prototypes and familiarity with responsible AI concepts such as fairness, safety, and transparency.