Career in Machine Learning Engineering

Machine learning (ML) is the subgroup of Artificial Intelligence (AI). The ML aims to build systems that learn and improve performance based on data. Often, Machine Learning and AI are discussed together. Sometimes the terms ML and AI are used interchangeably, however, they don’t mean the same thing. In the modern world, ML is all around us. When we do banking, shop online, or use social media, machine learning algorithms come into play to make our experience efficient, smooth, and secure. Machine Learning Engineers work with algorithms, data, and artificial intelligence.

Prerequisites for Machine Learning (ML) Engineer

Knowledge of programming languages such as Python, R, Java, JavaScript, etc.
Knowledge of linear algebra, statistics, probability and calculus.
Knowledge of how to clean and structure raw data to the desired format to reduce the time taken for decision-making.

Types of Machine Learning

Supervised Machine Learning: This is a frequently used method. In this model a data scientist acts as a guide and teaches the algorithm what conclusions it should make. In supervised learning, the algorithm is trained by a dataset that is already labelled and has a predefined output.
Unsupervised Machine Learning: Unsupervised machine learning uses a more independent approach, in which a computer learns to identify complex processes and patterns without a human providing close, constant guidance. Unsupervised machine learning involves training based on data that does not have labels or a specific, defined output.

ML Engineers' Responsibilities

While job responsibilities for machine learning engineers will differ, they often include:

Implementing machine learning algorithms
Running AI systems experiments and tests
Designing and developing machine learning systems
Performing statistical analyses

Job Prospects for Machine Learning Engineers

Over the past few decades, the computer science field has seen constant growth. According to the US Bureau of Labor Statistics, information and computer science research jobs will grow 23% through 2032. This forecast is for the USA alone. Opportunities will be limitless in this field. In India, Machine Learning Engineers will be in demand in the coming years.

How to become a machine learning engineer?

To become a ML Engineer you can follow these steps:

1. Earn a bachelor's degree in computer science or a related field like Mathematics and Statistics etc.
2. Gain entry-level work experience. Some entry-level positions that can lead to a machine learning career include:

Computer engineer
Data scientist
Software developer
Software engineer

3. Build your machine learning expertise.
While working in a related role, you can build specialised experience to prepare you for machine learning engineering. Consider working on machine learning projects to practice essential skills or earning relevant certifications.