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Engineering Intern — ML / LLM

ML / LLM Internship

Intern Internship On-site / Hybrid — Kolkata, West Bengal, India 3 months

Engagement

Internship

Structured, hands-on mentorship for a fixed term. This internship is on site at Kolkata, with hybrid days available by prior arrangement. It is not a remote position.

Scope of role

Contribute to live projects. Shadow senior practitioners. Build a portfolio that matters.

Please note this is an unpaid internship — the offer is real work, mentorship and experience at the frontier, not a stipend.

01 — The role

Why this role exists at EduRankAI

3 months on the AI platform team. Own a slice — eval harness, retrieval pipeline, fine-tune, prompt engineering. Real research or applied work, paired daily with Staff ML engineers. The bar is "you build something the team continues to use after you leave". An eval that finds a regression we did not know about. A retrieval pipeline that improves a number we measure. A fine-tuning run that produces a model the team ships.

02 — The work

What you will own

  • 01 Own a scoped ML deliverable for 3 months.
  • 02 Ship something the team uses after your internship ends.
  • 03 Author a technical report at the level the team would publish externally.
  • 04 Pair daily with Staff ML engineers.
  • 05 Present what you built at end-of-internship review.

03 — The expertise

What we look for

Python + PyTorch at intermediate levelOne ML/LLM project shipped (course, OSS, paper)Strong reading + writingCuriosity to debug at the model levelEvaluation-first mindset

04 — The bar

Who thrives here

  • You have at least one ML or LLM project you can point at that another person has used.
  • You have read at least three ML papers carefully and can describe their load-bearing claim.
  • You can describe a specific ML bug you debugged at the model level, not at the API level.
  • You write evaluation code on purpose.
  • You can defend the design of an eval you wrote in writing for 30 minutes.

Terms of Engagement

How this internship is structured

6 days a week, about 40 hours of total engagement — 5 hours a day of project work and departmental responsibilities, plus 1 hour 40 minutes a day of holistic well-being and personal development.

Type

Full-Time

Working days

6 per week

Rest days

1 per week

Total engagement

~40 hrs/week

Project work

5h per day

Well-being

1h 40m per day

Duration

12 weeks

Project work and departmental responsibilities and holistic well-being and personal development together make up the total engagement above — the total is not all task output. Well-being time covers physical fitness, mindfulness, reading, reflective learning, leadership development and community engagement. About 480 hours of total engagement over 12 weeks — 360 hours of project work and 120 hours of well-being and personal development.

Measured by

Weekly mentor review against a published rubric, plus the completion of the recorded hours. Working materially over the commitment is treated the same as working under it.

Where this stands legally

Offered under the applicable AICTE internship framework, where one academic credit corresponds to a minimum of 45 hours of work — which is why these hours are counted and certified. The engagement sits well inside the 9-hour day and 48-hour week ceiling of the applicable state Shops and Establishments Act, and the seventh day is a full rest day.

At a minimum of 45 hours of work per academic credit, this engagement is equivalent to roughly 10.7 credits. Your institution decides what it awards; EduRankAI records the hours and the work.

The full per-level model is published at Working Hours by Level.

05 — Hiring process

What to expect after you apply

  1. 01

    Application review

    Every application is read personally within five business days. We respond either way.

  2. 02

    Take-home or live exercise

    Role-specific. Time-boxed. Real problems we are actually working on, not invented puzzles.

  3. 03

    Conversations

    Deep technical and values conversations with the team you would join. No trick questions. No panel ambushes.

  4. 04

    Offer or honest no

    If yes: digital offer letter, signed in-portal, transparent terms. If no: written feedback if you want it.

Before you start

What we will collect. What it costs. What we will not do with it.

We will collect

  • Name, email, phone — Account + application updates. No marketing.
  • Resume / portfolio link — Human review of your work.
  • Date + place of birth — Identity verification only.
  • Your written responses — Selection rubric. Read by humans.
  • Government ID (later) — Anti-fraud at offer / interview stage. Not at signup.

We will never

  • Sell your data
  • Share with third-party recruiters
  • Use for advertising
  • Train models on it
  • Send marketing email

Our situation

EduRankAI is a small, independent organization building long-term capabilities in educational intelligence, advanced AI systems, and research infrastructure. We take no advertiser money, no donations with strings attached, and no investor pressure on hiring decisions. Applying is free, and every application is read by a human — recruitment, technical, academic and leadership teams. It buys us the right to be honest.

Full transparency policy Questions? Email us

Ready to apply?

We read every application personally. If you are the right person for this role — regardless of pedigree, background, or where you are based — you will hear back from us within five business days.

Intern Internship

Engineering Intern — ML / LLM

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