Salary · India LPA
Machine Learning Engineer salary in India
MLE pay sits above pure data science when production serving, monitoring, and rollback stories are real. Kaggle-only profiles rarely clear product MLE bands at 3+ YOE.
LPA bands by experience
Ranges reflect mixed services + product hiring — not top-decile outliers or internship stipends.
| Experience | Typical fixed CTC band |
|---|---|
| 0–2 years | 8–14 LPA |
| 3–5 years | 14–26 LPA |
| 5–8 years | 22–40 LPA |
City and remote notes
- Bengaluru (BLR): product AI teams often +15–20% vs national mid
- Hyderabad (HYD): GCC ML platform roles growing; near BLR for MNCs
- NCR (Delhi NCR): fintech AI; upper band for serving-scale roles
- Pune: limited product MLE; usually below BLR peak
- Remote (India): remote MLE for US product can significantly exceed local bands
Negotiation tip
Ask how much time is research vs on-call for model serving — many 'MLE' roles in India are 50% data engineering; align title and band with actual pipeline ownership.
Related reading: Salary negotiation in India · SDE salary by YOE
FAQ
What is Machine Learning Engineer salary in India?
Honest bands: 0–2 YOE 8–14 LPA, 3–5 YOE 14–26 LPA, 5–8 YOE 22–40 LPA at product AI teams with deployed models.
MLE vs Data Scientist — who earns more?
Often similar bands at the same company, but MLE skews higher when the role owns serving infra and SLAs. DS-heavy research roles may pay similarly with different work mix.
How do MLEs negotiate offers?
Lead with latency, drift monitoring, and rollback incidents handled. Negotiate GPU budget, level (SDE vs MLE ladder), and bonus tied to production metrics not offline AUC.