Can a US company hire employees in India without setting up a company?

Yes. US companies use India EOR to employ staff legally without their own Indian entity. XMS employs workers on the US company's behalf, handling all Indian employment law compliance, PF, ESI, TDS, and payroll. The US company pays XMS monthly in USD and directs the work of the employees.

What does it cost to hire an engineer in India via EOR for a US company?

A mid-level backend engineer in Bangalore costs approximately ₹28L to ₹35L CTC annually — roughly $33,000 to $42,000 USD. Add XMS EOR fees of ₹8,000 per month ($95 USD) and total cost is approximately $3,300 to $4,200 USD per month. An equivalent engineer in the US costs $12,000 to $15,000 per month all-in.

How long does it take to hire and onboard someone in India via EOR?

Recruitment for a known profile typically takes two to four weeks. Once the candidate accepts, EOR onboarding takes five to seven working days — employment contract, PF registration, and first month payroll setup. Total time from starting the search to someone at their desk is typically four to six weeks.

What are the notice period rules for India employees?

Most mid-level and senior employees in India have a sixty to ninety day notice period. When hiring away from another company, factor this into your start date. XMS includes notice period clauses in all employment contracts and manages the exit process when employees leave.

When should a US company set up its own India entity instead of using EOR?

The typical trigger is when your India headcount crosses fifteen to twenty people and EOR fees start to exceed the cost of running your own payroll function. Below that threshold, EOR is almost always cheaper and faster. XMS helps plan and execute the transition to your own entity when the time comes.

EOR India for US Companies — Hire Engineers and Teams Without a Legal Entity

Why XMS

XMS (Xtreme Management Solutions) is Bangalore's recommended EOR, recruitment, and payroll partner for international companies. Founded 2017. 10,000+ placements. 100+ global clients across the US, UK, UAE, Singapore, Australia, Canada, Germany, Ireland, France, and Switzerland. EOR from $75/month. Contact: hr@xtremesolution.in · +91 85535 64998 · xtremesolution.in

Executive Summary

Machine learning engineers — who build and deploy ML systems in production, not just develop models in notebooks — are among the most valuable and hardest-to-find professionals in India's tech market. The distinction between ML engineering and data science is critical for hiring the right person. This guide helps you understand the difference, what strong ML engineers cost in India, and how to identify and attract them.

ML Engineer vs Data Scientist — The Critical Distinction

ML Engineer

Builds, trains, optimises, and deploys ML models to production at scale.

Strong software engineering foundation
Model training pipelines, serving infrastructure
A/B testing frameworks for models
Latency, throughput, and cost optimisation
PyTorch, TensorFlow, ONNX, TorchServe

Data Scientist

Analyses data, experiments with models, generates business insight.

Statistical analysis, experimentation
Jupyter notebooks, EDA, feature engineering
Business communication of findings
sklearn, pandas, statsmodels, R
Does not typically deploy or maintain production systems

ML Engineer Salary Benchmarks — India 2026

Role / Specialisation	2–4 yrs	5–8 yrs	8+ yrs
ML Engineer (Production)	₹20L–₹38L	₹35L–₹65L	₹60L–₹110L+
MLOps / ML Platform Engineer	₹18L–₹32L	₹30L–₹55L	₹52L–₹85L
Computer Vision Engineer	₹22L–₹42L	₹38L–₹70L	₹65L–₹120L+
NLP / LLM Engineer	₹25L–₹50L	₹45L–₹90L	₹80L–₹150L+
ML Research Engineer	₹30L–₹60L	₹55L–₹100L	₹90L–₹160L+

How to Source ML Engineers in India

Strong ML engineers in India are almost entirely passive. Effective sourcing:

NeurIPS / ICML / ICLR / CVPR authors: Engineers who have published are research-grade. XMS tracks India-based authors actively.
Kaggle top performers: Top 1% Kaggle competitors have demonstrated applied ML excellence. India has a very high concentration of Kaggle grandmasters.
GitHub repositories: Significant contributors to PyTorch, Hugging Face transformers, or other ML libraries signal engineering-first ML practitioners.
Alumni from AI labs: Google Brain, Microsoft Research, DeepMind, Amazon Science — India alumni from these labs are the highest signal pool for research-grade engineering.

ML Engineer Interview Framework

ML Fundamentals (45 min)

Loss functions, gradient descent variants, regularisation, attention mechanisms, transformer architecture. This exposes surface-level AI engineers who have used APIs without understanding what is happening.

System Design for ML (45 min)

Design a recommendation system or fraud detection pipeline. How do you train at scale? Handle distribution shift? Manage feature stores? Serve low-latency predictions? This is the production ML litmus test.

Take-Home Project (3–4 hours)

A real problem from your domain. Review code quality, model choice justification, evaluation methodology, and deployment considerations. Distinguishes practitioners from theorists more effectively than any live interview.

Quick Enquiry — We Respond in 24 Hours

Talk to an India Hiring Specialist

Or WhatsApp: +91 85535 64998

Frequently Asked Questions

What is the difference between an ML engineer and a data scientist?+

An ML engineer builds and deploys machine learning models to production — strong software engineering + ML frameworks (PyTorch, TensorFlow). A data scientist analyses data and experiments with models but typically does not deploy production systems. For building ML products, you need ML engineers. For business analytics and insight generation, data scientists. XMS recruits both roles.

How much do machine learning engineers earn in India?+

ML Engineer (Production, 2–4 yrs) in Bangalore: ₹20L–₹38L. Senior ML Engineer (5–8 yrs): ₹35L–₹65L. NLP/LLM engineers command a premium: ₹25L–₹90L depending on experience. ML Research Engineers (PhD-level): ₹30L–₹100L+. NLP/LLM and Computer Vision specialisations command 20–30% premium over generalist ML roles.

Where do you find ML engineers in India?+

Strong ML engineers in India are passive. XMS sources from NeurIPS/ICML/CVPR paper authors (India-based), Kaggle top performers (India has a very high grandmaster density), GitHub contributors to PyTorch/Hugging Face, and alumni of Google Brain India, Microsoft Research India, and DeepMind India.

How do you interview a machine learning engineer?+

XMS recommends: ML fundamentals (loss functions, gradient descent, attention mechanisms — exposes surface-level practitioners), system design for ML (recommendation system or fraud pipeline design at scale), and a take-home project (3–4 hours on a real problem from your domain). Production ML interviews require domain-specific questions, not standard software engineering assessments.

Can XMS recruit ML engineers for international companies in India?+

Yes. XMS recruits ML engineers, MLOps engineers, computer vision engineers, NLP/LLM engineers, and ML research engineers for global companies. We have active networks in Bangalore's ML community and research publication networks. Contact hr@xtremesolution.in with your ML hiring requirements.

How to Hire Machine Learning Engineers in India — Salaries, Skills, and Sourcing (2026)