I
IDfy
Product Intern
Skills
Machine LearningAICompliance
2 months ago
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Important information
Contract type:
Permanent
Location:
Mumbai, Maharashtra, India
Work mode:
Onsite
Published on:
9 September 2026
What they need
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 strong 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 strong ownership mindset, high curiosity, and thrive in a fast-paced product environment.
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