What does a Machine Learning Engineer do?
A machine learning engineer builds, deploys and maintains machine-learning models in production at scale. In India they typically combine software engineering with ML, taking models from research into reliable services — building training pipelines, optimising inference, monitoring model performance and drift, and ensuring AI features run efficiently and reliably for real users in live applications.
A machine learning engineer usually has around 1–8 yrs of experience and earns typically ₹7L–₹35L/yr in India. The day-to-day blends Python, TensorFlow / PyTorch, MLOps and more — this page gives you a ready-to-use machine learning engineer job description template you can copy, plus the exact skills and salary employers expect.
Machine Learning Engineer job description template
Copy the 8 responsibilities, 5 requirements and 9 skills below into your job post, then edit the parts that are specific to your company — pay band, location and reporting line.
Select the text above to copy it manually if the button is unavailable.
What are a Machine Learning Engineer's key responsibilities?
A machine learning engineer is typically responsible for the 8 duties below, which cover the day-to-day work most employers expect the role to own outright. Paste them into your job post as they are, or cut the ones another team already handles — a responsibility list that claims work the hire will not actually do is the fastest way to lose a candidate at offer stage:
- Take models from prototype to production-grade, scalable services
- Build and automate training, evaluation and deployment pipelines (MLOps)
- Optimise model inference for latency, throughput and cost
- Monitor models in production for accuracy, drift and data quality
- Engineer features and data pipelines that feed model training
- Collaborate with data scientists to productionise their experiments
- Implement A/B testing and rollback strategies for model releases
- Integrate ML services into applications via APIs
What qualifications does a Machine Learning Engineer need?
Employers hiring a machine learning engineer in India usually ask for the 5 qualifications below, typically alongside 1–8 yrs of experience. Keep only the ones you will genuinely screen on: every extra must-have narrows the pool, and in the Indian market a long mandatory list filters out strong candidates whose background simply reads differently on paper:
- Strong software-engineering skills plus solid machine-learning fundamentals
- Proficiency in Python and an ML framework (TensorFlow or PyTorch)
- Experience deploying and serving models, plus MLOps tooling
- Understanding of data pipelines, containers and cloud ML services
- Knowledge of model evaluation, versioning and monitoring
What skills should a Machine Learning Engineer have?
These are the 9 skills employers name most often on live machine learning engineer listings in India. Treat the first few as the ones worth screening for directly and the rest as signals a candidate can pick up on the job — asking for all of them at once is what turns a reasonable role into an unfillable one:
Listing the three or four skills you genuinely screen on — rather than all 9 — is what keeps a machine learning engineer posting from filtering out candidates who could do the job.
What does a Machine Learning Engineer earn in India?
Typical salary (India)
typically ₹7L–₹35L/yr
Experience range
1–8 yrs
These are typical ranges and vary by city, company and skills. For live, role-specific pay data, see the OnJob salary guide.
Machine Learning Engineer job description — FAQs
What does a machine learning engineer do?
A machine learning engineer builds and deploys ML models into production so they run reliably at scale. The work blends software engineering with ML — building training and serving pipelines, optimising inference, and monitoring models for drift and accuracy in live systems.
What is the difference between an ML engineer and a data scientist?
A data scientist focuses on analysis and building models to answer questions; an ML engineer focuses on deploying, scaling and maintaining those models in production. ML engineers lean more toward software engineering and MLOps.
What is MLOps?
MLOps is the set of practices and tools for reliably deploying, monitoring and maintaining machine-learning models in production — covering versioning, automated training/deployment pipelines, monitoring for drift, and rollback. It's a core skill for ML engineers.
How much does a machine learning engineer earn in India?
Entry-level ML engineers typically earn ₹7L–₹14L per year, mid-level ₹16L–₹26L, and senior ML/AI engineers ₹30L+. Machine learning engineers command the top of that range when they can ship rather than prototype: production serving pipelines, MLOps automation for training and deployment, inference tuned for latency and cost, and monitoring that catches drift before users notice. Advertised experience commonly runs 1–8 years.