Karya Research Intern Role in AI Evaluations
Karya is hiring a Research Intern for its AI Evaluations team in Bengaluru, with a focus on how language technologies work for Indian communities. The opportunity is aimed at social-science students and recent graduates who want to study the real-world behavior of speech, text, and translation systems. The role brings research into direct contact with engineering work, so the intern will contribute across the build-and-evaluate lifecycle. It is designed for candidates who can think carefully about technology, people, and context, especially in rural and low-resource settings. The listing also notes flexible work options and other benefits, while not stating a stipend, duration, or application deadline.
The position stands out because it does not require a technical degree or coding background. Instead, it looks for applicants who can use research methods, understand AI and machine learning concepts, and engage with the social dimensions of language technologies. This makes the role especially relevant for candidates from social-science and interdisciplinary backgrounds. The work is centered on evaluation, methodology, and community interaction rather than software development alone. For applicants interested in AI systems and their impact on Indian communities, the internship offers a research-oriented entry point.
What the Research Intern Will Do
The Research Intern will help evaluate speech, text, and translation systems using qualitative, quantitative, or mixed research methods. The role is not limited to one kind of analysis, which means the intern may work with different approaches depending on the question being studied. A major part of the work is to help develop testing methodologies that can be used to assess how these systems behave. The intern will also investigate how technology interacts with rural and low-resource communities, which places community context at the center of the research process.
Another important aspect of the role is collaboration with engineers. The intern will work alongside engineering teams across the build-and-evaluate lifecycle, which suggests that research is expected to inform system development rather than sit apart from it. This kind of work requires attention to both technical behavior and human experience. It also means the intern may need to translate research findings into practical feedback that supports evaluation and improvement. The listing presents the role as one that connects research design, system testing, and real-world use.
Core work areas mentioned in the listing
- Evaluating speech systems
- Evaluating text systems
- Evaluating translation systems
- Applying qualitative, quantitative, or mixed methods
- Helping develop testing methodologies
- Studying technology use in rural and low-resource communities
- Working with engineers across the build-and-evaluate lifecycle
The role is therefore broad in scope but clearly anchored in evaluation. Rather than focusing only on one dataset or one model, the intern is expected to think about how language technologies perform in context. That includes understanding how systems are tested, what kinds of evidence are useful, and how community realities shape outcomes. The emphasis on Indian communities makes the work especially relevant to local language and social settings. It is a research internship with direct practical implications for AI evaluation.
Who Can Apply and What Background Fits
The internship is intended for applicants who are pursuing or have recently completed an undergraduate or master's degree in specific social-science and interdisciplinary fields. The eligible backgrounds listed are Sociology, Anthropology, Development Studies, Gender Studies, Political Science, Economics, and Science and Technology Studies. This signals that the role is built for candidates who already have training in studying people, institutions, and systems. The listing does not require a technical degree, which broadens access for students and graduates from non-engineering paths.
Even though coding is not required, applicants should understand AI/ML concepts well enough to discuss model evaluation, human-in-the-loop systems, and language technologies. This means the role expects conceptual familiarity with how AI systems are assessed and how humans participate in those systems. The emphasis is on being able to discuss and analyze these ideas, not on writing code. In other words, the internship values research literacy and systems understanding alongside social-science training. Candidates who can connect technical ideas with social consequences are likely to fit the role well.
Eligible academic backgrounds
- Sociology
- Anthropology
- Development Studies
- Gender Studies
- Political Science
- Economics
- Science and Technology Studies
The listing also points to several qualities that matter in practice. Research training is relevant, as is comfort with focus-group discussions and field visits. The role also values socio-technical systems thinking, communication ability, and comfort with ambiguity. These traits suggest that the intern may need to navigate open-ended questions, varied settings, and evolving research needs. The work is likely to involve both structured analysis and flexible problem-solving.
Skills, Research Methods, and Preferred Strengths
Another key strength is the ability to think in terms of socio-technical systems. That means seeing AI not only as a technical artifact but also as something shaped by people, institutions, and context. The role also calls for good communication ability, which is important when working with engineers and when discussing research findings. Comfort with ambiguity is also relevant, since evaluation work often involves questions that do not have simple answers. The listing suggests that the intern should be able to work through uncertainty while keeping the research goal in view.
Relevant strengths mentioned in the listing
- Research training
- Comfort with focus-group discussions
- Comfort with field visits
- Socio-technical systems thinking
- Communication ability
- Comfort with ambiguity
There are also a few advantages that can strengthen an application. Multilingual proficiency in Indian languages is listed as an advantage, which fits the role’s focus on language technologies and Indian communities. Computational social-science experience is also mentioned as an advantage, suggesting that applicants with some experience at the intersection of social research and computation may stand out. These are not stated as requirements, but they align closely with the work described. They may help candidates contribute more effectively to evaluation and methodology discussions.
The overall skill profile is interdisciplinary rather than narrowly technical. The listing makes clear that understanding AI/ML concepts matters, but the emphasis remains on research judgment, communication, and contextual awareness. Candidates who can discuss model evaluation and human-in-the-loop systems while also handling field-based or community-based research may be especially aligned with the role. The internship appears to value thoughtful analysis over coding ability. That combination makes it distinctive among research opportunities in AI.
Why the Role Matters for Indian Language Technology Research
This internship is centered on a specific and important question: how language technologies work for Indian communities. The listing makes that focus explicit by connecting evaluation work to speech, text, and translation systems. It also highlights rural and low-resource communities, which suggests attention to settings where technology may behave differently or where data and infrastructure may be limited. The role therefore goes beyond generic model testing and looks at how systems perform in social contexts that matter locally.
Because the intern will work with engineers across the build-and-evaluate lifecycle, the research is likely to influence how systems are developed and assessed. That makes the role important not only for understanding outcomes but also for shaping them. The mention of human-in-the-loop systems and model evaluation shows that the team is interested in how people and technology interact. In this setting, research can help reveal where systems work well, where they struggle, and how evaluation methods should be adapted. The internship is thus positioned at the intersection of language, technology, and social research.
Contextual focus of the role
- Indian communities
- Speech systems
- Text systems
- Translation systems
- Rural communities
- Low-resource communities
The role is also meaningful because it welcomes candidates from social-science backgrounds into AI evaluation work. That matters in a field where technical perspectives often dominate. By asking for research training, field comfort, and socio-technical thinking, the listing shows that evaluation can benefit from people who study human behavior and social systems. The internship therefore creates space for interdisciplinary work without requiring coding. It is a research opportunity built around the idea that language technologies should be examined in relation to the communities they serve.
The official listing also mentions flexible work options and other benefits, which may appeal to applicants looking for some adaptability in how they work. At the same time, the listing does not provide a stipend, duration, or application deadline. Those details are simply not stated, so applicants would need to rely on the official listing for any further information. What is clear is the role’s focus on evaluation, methodology, and community-centered research. That makes it a strong fit for candidates interested in the social life of AI systems.
Application Fit and Role Summary
The internship is also notable for its emphasis on Indian languages and communities. Multilingual ability is an advantage, as is computational social-science experience, but the core requirement is a strong research mindset. The work involves evaluating systems, helping design testing methods, and collaborating with engineers. That combination makes the role both analytical and applied. It is a research internship with direct relevance to how AI systems are understood and improved in context.
Frequently Asked Questions
What is Karya hiring for?
Karya is hiring a Research Intern for its AI Evaluations team in Bengaluru. The role focuses on examining how language technologies work for Indian communities. The intern will help evaluate speech, text, and translation systems and contribute to testing methodologies.
What kind of research methods are expected?
The listing says the intern will use qualitative, quantitative, or mixed research methods. The role is centered on evaluation and methodology, so the candidate should be comfortable using research approaches that help assess how systems behave in context.
Which academic backgrounds are eligible?
Applicants should be pursuing or have recently completed an undergraduate or master's degree in Sociology, Anthropology, Development Studies, Gender Studies, Political Science, Economics, or Science and Technology Studies. A technical degree is not required.
Is coding required for this internship?
No, coding is not required. The listing specifically says a technical degree and coding are not needed. However, applicants should understand AI/ML concepts well enough to discuss model evaluation, human-in-the-loop systems, and language technologies.
What skills are considered relevant?
Relevant skills include research training, comfort with focus-group discussions and field visits, socio-technical systems thinking, communication ability, and comfort with ambiguity. Multilingual proficiency in Indian languages and computational social-science experience are listed as advantages.
Does the listing mention stipend, duration, or deadline?
No, the official listing does not state a stipend, duration, or application deadline. It does mention flexible work options and other benefits, but those missing details are not provided in the content.
Conclusion
Karya’s Research Intern role in Bengaluru is a focused opportunity for social-science students and recent graduates who want to study language technologies in Indian contexts. The internship brings together evaluation, methodology, community interaction, and collaboration with engineers, all without requiring a technical degree or coding background. It is especially relevant for candidates who can think across social and technical dimensions, work with ambiguity, and engage with rural or low-resource communities. With its emphasis on speech, text, and translation systems, the role offers a clear path into AI evaluations for applicants with interdisciplinary research interests. The listing’s flexible work options and other benefits add to its appeal, while key details like stipend, duration, and deadline remain unstated.
