AI Security Intern – Paid Internship

3 days ago

Bengaluru, Karnataka, India Phygitalytics Full time ₹ 6,00,000 - ₹ 18,00,000 per year

Company Description

Phygitalytics Consulting transforms data into intelligent solutions by combining human imagination with AI capabilities. With deep expertise in GenAI, ML, and data strategy, we empower organizations to build confidently in the age of intelligence.

We are looking for an AI Security Intern to join our team, with a focus on evaluating AI models, testing them from applied domain contexts, and strengthening security posture. This internship blends practical applied use cases with research-oriented outcomes.

Role Description

  • Conduct model evaluation and testing of LLMs and GenAI systems for robustness, safety, and reliability.
  • Experiment with content moderation APIs and assess model behavior in sensitive or high-risk domains.
  • Design and run domain-based experiments (e.g., healthcare, retail, finance, education) to explore risks, failure cases, and improvements.
  • Support the development of a preprint paper or whitepaper on AI security and evaluation practices.
  • Collaborate with mentors to gain exposure to LLMOps pipelines, evaluation frameworks (e.g., Giskard), and observability tools.

Tools & Exposure

  • AI evaluation frameworks such as Giskard and red-teaming toolkits.
  • Content moderation APIs from leading providers.
  • Hands-on work with LLMOps / model testing pipelines.
  • Learning best practices in responsible AI adoption and enterprise-grade observability.

Qualifications

  • Currently enrolled in a Bachelor's or Master's degree program in Computer Science, Data Science, AI/ML, Cybersecurity, or a related field.
  • Knowledge of AI and ML concepts is a plus.
  • Familiarity with Python and ML libraries is desirable.
  • Strong interest in AI security, model evaluation, and applied use cases.
  • Curiosity about responsible AI, governance, and safety frameworks.

Why Join

  • Paid internship with hands-on applied learning.
  • Blend of research and real-world projects.
  • Direct exposure to AI security practices and tools.
  • Opportunity to co-author a research output (preprint or whitepaper).

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