Location
Ahmedabad, Gujarat
Work Mode
Hybrid
Duration
4 months
Stipend
₹19,000/mo
Start Date
Immediate / Rolling
Openings
8 positions
Type
Full-time
Category
Generative AI
About the Internship
K7 Computing is hiring a RAG Pipeline Engineer Intern in Ahmedabad — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to retrieval-augmented generation pipelines rather than a certificate-only programme.
About the role
As a RAG Pipeline Engineer Intern…
About K7 Computing
K7 Computing offers a mentor-led RAG Pipeline Engineer Intern in Ahmedabad with live project work in generative ai, a stipend of ₹19,000/month and a Pre-Placement Offer opportunity for strong performers.
See all K7 Computinginternships →Ahmedabad, GujaratVerified employer8 openings
Apply to K7 Computing →Skills Required
Retrieval-Augmented Generation (RAG)EmbeddingsVector Databases (Pinecone / Qdrant)PythonChunking & IndexingLlamaIndex / LangChainHybrid SearchCitation & GroundingEvaluation MetricsDocument Parsing
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech (CSE/IT/AI-ML), MCA or M.Sc (Computer Science / Data Science) who are based in or willing to work from Ahmedabad. You should be keen to learn Retrieval-Augmented Generation (RAG), Embeddings, Vector Databases (Pinecone / Qdrant) on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.
Perks
Exposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship Certificate
Interview & Selection Process
4 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Technical interview on fundamentals and your projects
- 3Practical assignment or case study with a short walkthrough
- 4HR discussion — stipend, start date, expectations and offer
₹19,000/month
Stipend · 4 months
Openings8 positions
Applicants0 applied
ModeHybrid
CategoryGenerative AI
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