Machine learning engineers are the creators of self-running software that allows machines to automate predictive models.
ML applications, irrespective of direct programming, learn and become accurate from experiences, exactly how humans do. When exposed to new data, these applications discover, develop, and modify themselves to give a better experience.
Moving ahead in this article, you will learn more about what a machine learning engineer does, the career scope, the skills required, and the role of artificial intelligence and data science in this domain.
Who is a Machine Learning Engineer?
Machine learning engineers are the creators of self-running software that provides machines with the capability to automate predictive models.
ML applications, irrespective of direct programming, learn and become accurate from experiences, exactly as humans do. These applications, when exposed to new data, discover, develop, and modify themselves to give a better experience.
Here are two examples to help you understand this better.
Consider you are looking for certification courses on Google. After a couple of searches and skips, Google automatically starts suggesting courses that match what you are looking for. And this is what a machine learning engineer does.
Similarly, when you ask Alexa to play your favourite part of a song, the algorithm is designed such that, it will go through your most played and select one from there. The experience will further improve as you keep telling her to skip the songs, repeat the songs, modify the volume, and many such commands.
What Does a Machine Learning Engineer Do?
A machine learning engineer job includes the combined work of a data scientist and software engineer. While a data scientist’s job is more analytical and more into mathematical, statistical, and analytical datasets, software engineers have the upper hand regarding codes and programs for designing software systems. Now an ML engineer is someone who can bring the best of both worlds to the table.
The typical job responsibilities of an ML engineer are:
- Consulting and analysing the machine learning objectives and then picking the best approach to formulate the data for analysis.
- Incorporating source data into machine learning systems to enable machine learning training.
- Collaborating with data scientists and building data science prototypes by applying suitable ML algorithms and tools for effective data pipelines.
- Managing, scaling, maintaining, and improving the ML model to ensure that the algorithms developed are accurate.
- Communicating with key people to understand the requirements and, depending on it, optimise the ML samples to work accordingly.
- Conducting tests, executing statistical analysis, and interpreting the test results for better performance and outcome.
Machine Learning Engineer Skills Required
The main goal of an ML engineer is to work on improving the machine learning accuracy and thus provide a better experience to the users. Hence to succeed as a Machine Learning Engineer, one must have the combined knowledge and skill sets of a software engineer and a data scientist. Listed below are the general skills for the job role.
- Knowledge of data structures, data modelling & software architecture.
- Data-related skills; command of programming languages like Python and Java, to estimate and predict algorithms and prototypes.
- Software engineering skills, i.e., good command of algorithms, data structures, and computer architecture.
- Exceptional mathematical and statistical skills, to perform estimations and operate with algorithms.
- Written and verbal communication skills to explain the complicated process to people who are not programming specialists.
- Ability to work with large and complex datasets along with a team.
- Problem-solving skills and knowledge of machine learning tools and resources like park and Hadoop, Kafka, R programming, MATLAB, etc.
How much does a Machine Learning Engineer Earn?
Machine learning engineers design self-running artificial intelligence-based software to automate predictive prototypes for suggested searches, chatbots, translation apps, virtual assistants, driverless cars, and so on. Thus, the demand for ML engineers is increasing with the evolution of technology and advancement in data science and data analytics domain.
Organisations nowadays choose to work with machine learning experts to enhance products and services. Working with technology and AI helps organisations to outgrow the competition and provide innovative solutions. A machine learning engineer’s salary in India starts from around ₹ 3 to ₹ 4 Lakhs and goes up to ₹ 21 to ₹ 22 Lakhs [Source].
The average annual salary lies somewhere around ₹ 7 to ₹ 10 Lakhs [Source]. The salary, however, keeps on increasing with experience and expertise.
Machine Learning Engineer Career Scope
Machine learning has a wide range of applications be it video surveillance for security purposes or facial recognition on your smartphone, tablets, or even laptops. Even social media platforms like Facebook, LinkedIn, Instagram, etc., use machine learning technologies to target promotions, advertisements, and related posts to their users based on their choices, likes, and posts to the website.
Similarly, YouTube, and various OTT platforms like Netflix, and Amazon also use ML and AI technologies to provide recommendations to users based on their searches, skips, and selection. Shopping websites like Flipkart, Amazon, Myntra, and various others use ML algorithms to suggest things to buy using the customer’s purchase and viewing history.
Due to the specialised skill set, and knowledge machine learning engineers possess, they are among the best-paid engineers in the workforce. Thus, companies like Intel, Apple, Facebook, LinkedIn, IBM, Spotify, and Google are among the prime recruiters of Machine Learning Engineers.
Quality of work, authority to make decisions, and expertise in algorithms and computer languages are the three prime indicators of a successful ML engineer. Hence, make sure you keep learning and developing your skills and be open to adapting to modern technologies. One of the best ways to do this is to undertake data science certification courses or executive programmes from a reputed institute.
Emeritus India offers a range of certification courses in data science in partnership with reputed Indian and international universities like IIM, IIT, XLRI and SPJIMR.
The curriculum of these courses is designed to help you gain an in-depth understanding and insights into AI and ML, acquire in-demand skills, and pace up with their growing importance across the world, which will ultimately help you grab lucrative opportunities with competitive pay packages.