Role Details:

Designation: Intern( Full time conversion basis performance)

Duration: 6 months

Location:Andheri East,Mumbai

Type: Work from office(Mon-Fri)

Stipend: 25k per month

Btech batch of 2025/2026 only preferred.

What your day would look like
Diving into real-world product problems, breaking down user needs, and driving feature definitions with a strong sense of ownership.
Exploring how applied ML and LLM techniques (RAG, embeddings, model evaluation, prompt and retrieval strategies) can enhance Privy's core modules, with plenty of hands-on experimentation.
Participating in live customer demos alongside leadership, listening to feedback from CXOs and product leaders, and turning it into real-world insights.
Building and testing AI-driven workflows, benchmarking model outputs on accuracy, speed, and cost tradeoffs, and constantly experimenting with emerging AI tools.
Learning fast: staying sharp on evolving AI/ML trends, applied ML and LLM techniques, and DPDP compliance frameworks.

We're the perfect match if you
Have hands-on project, research,



or internship experience with core ML tasks such as classification, NER, recommendation systems, or applied LLM/RAG projects, not just working with pre-built AI tools.
Understand ML fundamentals: model evaluation, precision/recall tradeoffs, data preprocessing, and reasoning about why a model behaves the way it does.
Have built with LLMs beyond basic prompting, such as RAG pipelines, embeddings/vector search, fine-tuning, or agentic workflows, using models like Claude, GPT, or similar.
Possess exceptional problem-solving skills, first-principles thinking, and robust quantitative/analytical ability.
Demonstrate strong business acumen: understanding the "why" behind features and how technology solves end-user pain points.
Show excellent written and verbal communication skills, with the ability to articulate complex technical ideas clearly to technical and non-technical audiences alike.
Possess a robust ownership mindset, high curiosity, and thrive in a quick-paced product environment.

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