Pune, Maharashtra
Hire machine learning engineers in Pune
Key facts
Shortlist
48 hours
Typical time to hire in Pune
21–40 days
Talent availability
Scarce — plan early
Salary bands
Machine learning engineers salaries in Pune
Junior
1–3 yrs
Mid
3–6 yrs
Senior
6–10 yrs
Lead
10+ yrs
Show as table
| Level | Pune |
|---|---|
| Junior (1–3 yrs) | ₹10–19 LPA |
| Mid (3–6 yrs) | ₹19–36 LPA |
| Senior (6–10 yrs) | ₹34–62 LPA |
| Lead (10+ yrs) | ₹57–90 LPA |
Indicative ranges compiled by Emplyify from market data, Q4 2026. They are a starting point for budgeting, not an offer benchmark; our Talent Index will replace them with pipeline data.
Notice periods in Pune
Most mid and senior engineers serve 60–90 days' notice. Service-company engineers commonly have 90 days; product-company engineers more often 30–60.
Local hiring notes
- Embedded and automotive software is a Pune strength — expect stronger supply than in other cities.
- Hybrid policies matter: commutes across Hinjewadi and Kharadi are long, and candidates ask about office days early.
- Counter-offers are common for senior engineers; we prepare candidates for them before the offer.
Where the talent works
Hinjewadi · Kharadi · Baner and Balewadi · Magarpatta and Hadapsar
GCC hiring in Pune →Our screen
Skills we vet for machine learning engineers
Good ML engineers are rare because the job is two jobs: modelling and production engineering. We screen for both — evidence of shipped models, not just Kaggle ranks.
| Skill | How we evidence it |
|---|---|
| Python and ML frameworks | Walk-through of a model they trained and deployed, including data and evaluation choices |
| LLM application engineering | Retrieval, evaluation and cost trade-offs on a real project |
| MLOps | How they versioned data and models, monitored drift and rolled back |
| Evaluation discipline | Offline vs online metrics, and a time a metric misled them |
| Software engineering | Code review of a past PR or a short live exercise |
Sample interview loop
A loop that respects candidates' time
1. Recruiter screen · 30 min
Motivation, notice period, CTC, must-have skills
2. Technical deep-dive · 60 min
Past systems, trade-offs, depth on core skills
3. Practical exercise · 60–90 min
Live problem or take-home review, never unpaid multi-day work
4. Hiring manager · 45 min
Team fit, ownership, communication
Screening questions we ask
- “Describe a model you shipped. How did you know it was working in production?”
- “When did you choose not to use an LLM, and why?”
- “How did you build an evaluation set for a retrieval or generation system?”
- “What broke after deployment, and how did you find out?”
Questions
Can you find engineers with production LLM experience?
Yes, but the pool is small and moves fast. We screen for retrieval, evaluation and cost control on real projects, not prompt demos, and we say upfront if your budget is below market.
Do you test candidates on ML theory?
Only as far as the role needs it. Our screen focuses on production decisions; your team can go deeper on theory in the technical round.
Is Pune a good location for a new GCC?
For automotive, embedded, enterprise software and BFSI technology, yes: talent depth is strong and costs are typically lower than in Bengaluru. For large senior AI teams, consider a hybrid plan with remote hires.
Two-minute brief
Hiring machine learning engineers in Pune?
We've pre-filled the role. A recruiter replies within 4 business hours; your shortlist follows within 48 hours.