Annual Report · 2026
State of Indian Engineering Placements 2026
An aggregation of NIRF 2024 placement disclosures across 100 ranked engineering institutions. Every chart is computed from the source dataset — published openly, citable, and downloadable.
Headline
Across 100 NIRF 2024-ranked engineering institutions, the median of median packages is ₹10 LPA, with the average median at ₹11 LPA. The average placement rate is 79.3% (median: 80%).
The headline (and most-quoted) number — the highest single offer in a season — tells a different story. The peak across the dataset is ₹350 LPA, while the median "highest package" across institutes is only ₹55 LPA. Headline packages are heavy-tailed; medians are what students and TPOs should plan against.
Who recruits everywhere?
Each NIRF disclosure lists 5–8 top recruiters. We counted unique appearances across all 100institutes. A company that appears on more disclosures has more campus presence — not more offers (NIRF doesn't publish offer counts).
Sector mix of top-recruiter mentions
Recruiters are classified into 6 sectors via a lightweight name-token mapping. Mentions are aggregated across the 100-institute dataset.
Median package by NIRF rank tier
Institutions grouped by NIRF rank band. The drop from Top-10 to Rank 61–100 is steeper on the median than on the highest-package number — i.e. tier difference shows up most for typical students, not the outlier offer.
Where the institutes are
State-wise count of NIRF-ranked engineering institutions in the 2024ranking.
Five institutes with the highest disclosed single offer
These are the outlier headline numbers. They make great press but are not what a student should plan around.
Methodology
All inputs come from NIRF 2024 Engineering Ranking, published by the Ministry of Education, Government of India. We extract the placement percentage, median package, highest package, and top recruiter list as disclosed by each institute.
Aggregations are deterministic and reproducible from the JSON snapshot. See /methodology for our full data-sourcing policy and /data-sources for the canonical list of primary sources we cite. Recruiter sector classification uses the token map in src/lib/recruiters.ts — a deliberately simple, inspectable mapping.
License
Report and dataset published under CC BY 4.0. You may reuse, adapt, and redistribute provided you cite this report and include a link back to the source page.
Suggested citation
PlacementPilot AI (2026). State of Indian Engineering Placements 2026. Retrieved from https://placementpilot.ai/research/state-of-indian-engineering-placements-2026.
Reproducing this report
The page is generated entirely from data/nirf-2024-engineering.json via src/lib/state-of-placements.ts. To re-run the aggregations locally: clone the repo, run npm install, then npm run build. The page at /research/state-of-indian-engineering-placements-2026 will re-render with current numbers.
Frequently asked
What is this report?
An aggregation of NIRF 2024 engineering placement disclosures across 100 ranked institutions. Every number on this page is computed deterministically from the source dataset and is reproducible from the downloadable JSON.
Where does the data come from?
NIRF 2024 Engineering Ranking, published by the Ministry of Education, Government of India. Each ranked institution self-reports placement data; we don't modify it.
Can I cite this report?
Yes. Suggested citation: "PlacementPilot AI (2026). State of Indian Engineering Placements 2026. Retrieved from https://placementpilot.ai/research/state-of-indian-engineering-placements-2026". Please include the date you accessed the page.
Is the underlying data available?
Yes. Download the JSON snapshot at https://placementpilot.ai/research/state-of-indian-engineering-placements-2026/data.json. License: CC BY 4.0 (attribution required). Source dataset is public NIRF disclosure.
How does PlacementPilot use this data?
We power our college pages (e.g. /colleges/iit-bombay/placements) from the same NIRF dataset. This report is the aggregate view; individual institute pages are the per-college view.
For TPOs and placement cells
PlacementPilot AI is the placement readiness platform for Indian engineering colleges — the same NIRF dataset powers the per-college pages used by TPOs.