You must have heard about Artificial Intelligence (AI) and Machine Learning (ML). These days, you can find these words in the news, on social media, and even in everyday speech. But have you ever thought, who creates these smart systems? The answer is – Machine Learning Engineers.
In this blog, we will talk in very simple words about:
- Who is a Machine Learning Engineer
- What work they do every day
- What skills they need
- How much they earn
- Why their job is so important
Let’s start!
Who is a Machine Learning Engineer?
A Machine Learning Engineer is a person who makes computers learn from data. Normally, when you write a computer program, you give step-by-step instructions. But a Machine Learning Engineer writes programs that can learn by themselves.
For example:
- You watch videos on YouTube, and it shows similar videos you may like.
- When you shop on Amazon, “Recommended for You” appears.
All this is possible because of Machine Learning Engineers.
They work like a bridge between Data Scientists (who study data) and Software Developers (who build apps). They must therefore comprehend both data and coding.
What Does a Machine Learning Engineer Do?
Their job is not only writing code. They do many things like:
1. Understand the Problem
First, they understand what the company wants.
Example:
- A bank wants to stop fraud.
- A shop wants to recommend products.
- A company wants to predict customer behavior.
They think:
- What data do we have?
- What result do we need?
- Which method will work best?
2. Collect and Clean Data
Data is like fuel for machine learning. But raw data is often messy.
So, they:
- Collect data from different sources.
- Remove mistakes or empty values.
- Arrange it in the correct format.
If data is clean, the result will be better.
3. Choose the Right Model
They decide which algorithm will work best.
Examples:
- Linear Regression → Predict prices.
- Decision Trees → Classify data.
- Neural Networks → For images and voice.
4. Train and Test the Model
They train the model using historical data. The model learns from patterns.
Then, they test it on new data.
If the accuracy is low, they improve it by adjusting settings.
5. Deploy the Model
After training, they put the model into real apps so people can use it.
Examples:
- A chatbot on a website.
- A fraud detection system in banking apps.
6. Monitor and Update
The job is not over after deployment. They check the model from time to time because data changes.
If performance drops, they train it again with new data.
Skills Needed to Become a Machine Learning Engineer
The following abilities are necessary if you wish to work as an ML engineer:
- Coding – Mostly in Python. (Other languages: R, Java)
- Math & Statistics – Basics of probability and algebra.
- Data Handling – How to manage big data.
- Machine Learning Algorithms – Like regression, clustering, neural networks.
- Cloud Tools – AWS, Google Cloud for deployment.
Don’t worry if it sounds tough now. You can learn step by step.
Where Do They Work?
Machine Learning Engineers work in many fields:
- Tech Companies – Google, Amazon, Microsoft.
- Healthcare – Predicting diseases, finding new medicines.
- Finance – Fraud detection, stock predictions.
- Retail – Personalized shopping experience.
How Much Do They Earn?
Good news – they earn a lot!
- In India, freshers can earn ₹8 to ₹20 lakh per year.
- In the US, average salary is about $110,000 per year.
With experience, salaries increase even more.
Future of Machine Learning Engineers
Machine Learning is the future. More companies want smart systems. Therefore, there is a rapidly increasing need for ML engineers.
Reports say jobs in this field will grow 30-40% in the next few years.
So, if you like coding and problem-solving, this is an amazing career.
