How Much Do Machine Learning Experts Make? (With Job Info)

Updated 26 January 2023

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Machine learning experts play a pivotal role in structuring data, analysing it and building efficient automated predictive models. The role is gaining prominence in various industries, like transportation, medicine, advertising and software development. Learning about this upcoming career can help you decide if it is a suitable choice for you. In this article, we discuss what machine learning experts do, enlist their skills, share how to become one and find out how much do machine learning experts make.

How Much Do Machine Learning Experts Make?

To answer the question, "How much do machine learning experts make?", it is important to note the average base salary of a machine learning expert varies depending on their exact role, where they work, their company and their experience. Machine learning experts know deep learning technologies and coding. This skill equips them to explore other career options. Some popular careers in machine learning are:

1. Software developer

National average salary: ₹44,334 per month

Primary duties: Software developers usually create digital tools and applications to meet specific project or client requirements. They understand backend system capabilities, write error-free code and ensure functionality in wireframes and designs. Sometimes, they also oversee the work of programmers, technicians and testers.

2. Computational linguist

National average salary: ₹6,87,776 per year

Primary duties: The role of a computational linguist aids features like voice recognition in systems. They develop computer systems that perform tasks like speech recognition, grammar checks and text mining. A computation linguist uses data mining principles and machine learning to develop software and tools. They also generally have a good understanding of linguistics to build powerful digital solutions.

3. Data scientist

National average salary: ₹8,50,429 per year

Primary duties: Data scientists gather and analyse extensive sets of structured and unstructured data. They use their knowledge in computer science, probability, statistics and mathematics to model data and make predictions. The insights provided by a data scientist usually help senior leaders make better business decisions.

4. Machine learning engineer

National average salary: ₹49,452 per month

Primary duties: A machine learning engineer creates predictive software and digital programs that take action without human interference. They may design, develop, test, troubleshoot and also maintain such software. A machine learning engineer generally collaborates with data scientists, data analysts and data administrators for their work.

5. Algorithm engineer

National average salary: ₹9,86,217 per year

Primary duties: An algorithm engineer improves intelligent digital systems by creating, analysing or installing new codes and algorithms. They usually work to create specific product features that serve specific business requirements. An algorithm engineer typically works along with data scientists, fellow algorithm engineers and clients.

6. Cybersecurity analyst

National average salary: ₹12,46,373 per year

Primary duties: A cybersecurity analyst protects the data of a company from any leaks or security threats. They understand security frameworks and help identify potential risks in storing or managing valuable business data. A cybersecurity analyst understands the prevalent protocols and best practices of storing data and works to continually strengthen a company's digital assets.

What Do Machine Learning Experts Do?

Machine learning experts are programmers who research, design, code and automate predictive tools and models. They are usually a part of the data science team in an organisation and work with data scientists, data analysts and data administrators. Machine learning experts usually build artificial intelligence (AI) systems that learn from large data sets and help make predictions.

The duties and responsibilities of a machine learning expert depend on the size of the organisation and the industry. Most machine learning experts perform most of the tasks as below:

Research, experiment and develop machine learning applications to meet business objectives
Perform statistical analysis on varied data sets and data models to test results
Identify errors and re-train machine learning systems
Research, identify and implement machine learning tools for better performance
Create data visualisations for better understanding
Enhance existing machine learning frameworks
Check data quality and clean using data cleaning techniques
Research and identify data sets for testing

How To Become A Machine Learning Expert?

You can follow these steps to become a machine learning expert:

1. Complete your education

Machine learning experts have comprehensive knowledge in mathematics, data science, computer science and computer programming. You may complete an under graduation in data science or any related discipline to improve your employability potential. In case you are already a graduate, you may take up specialised certificate courses to understand machine learning.

2. Build technical knowledge

Machine learning is an analytical and tech-driven role. It requires you to possess software skills, including Microsoft Azure, Google Cloud, Python, C++, Java, Spark, Hadoop and IBM Watson. Machine learning experts understand probability, statistics, data modelling and coding. Knowing data visualisation is also an essential requirement.

3. Gain work experience

The role of a machine learning expert is not an entry-level job. It requires experience in data science, coding and data analysis. You can gain this experience through internships after graduation, working on different projects and later through full-time jobs. Gaining professional experience can also help understand the industry standards and requirements, which helps advance your career.

4. Keep learning

The field of machine learning rapidly changes with technological advances. Therefore, it is important for machine learning experts to keep up with industry trends and continually upskill. With experience, machine learning experts gain business intelligence that qualifies them for higher leadership roles.

Technical Skills Required By A Machine Learning Expert

Machine learning experts combine software engineering principles with analytical theorems to devise machine learning models. They usually have strong business acumen, data science skills and software skills. Some of the technical skills that machine learning experts may possess to excel at their job are:

Multi-dimensional arrays
Computer architecture
Hypothesis-testing
Data modelling
Data architecture
Probability and statistics
Machine-learning algorithms like clustering, regression and classification
Neural networks
Calculus

Some essential tools that machine learning experts may use regularly are:

Python
Java
SQL
C++
Hadoop
Spark
TensorFlow
R Programming
Apache Kafka
Weka
MATLAB
IBM Watson

Soft Skills Required By A Machine Learning Expert

Machine learning experts are often a part of a team and may require several soft skills. A mix of technical skills and soft skills is usually necessary for a machine learning expert to thrive at their job. Some essential soft skills are:

Communication skills

Machine learning experts work with data scientists, data analysts and data administrators. They may also interact with the senior management to understand business objectives and build algorithms to match them. Machine learning experts quickly understand and communicate project goals, timelines and insights with all stakeholders. All of these tasks require strong communication and collaboration skills.

Problem-solving skills

Machine learning experts automate predictive models to solve specific business challenges. They understand business objectives and devise innovative solutions to address real-time challenges. Problem-solving using computational analytics is a foundational skill for machine learning experts.

Time management

Machine learning experts may work with several stakeholders and are required to organise their time to meet project deadlines. They usually spend most of their time training and re-training algorithms. They may also decipher ways to troubleshoot errors. Machine learning experts also require to plan projects, design software and perform tests. The role of a machine learning executive requires them to manage their time smartly and undertake many complex tasks simultaneously.

Leadership skills

Apart from working with cross-functional teams, machine learning experts may also mentor junior engineers. In this role, they usually guide junior machine learning experts and develop systems to train them. Developing leadership skills also helps machine learning experts improve business management and business decision-making skills.

Related: 10 Common Leadership Styles

The Work Environment Of A Machine Learning Expert

Machine learning experts work in various industries, including healthcare, transportation, advertising and finance. They typically have fixed working hours throughout the week but may work extra hours to deliver any urgent requirements. They spend most of their time in front of a computer screen working with complex systems. The job role is demanding and requires immense concentration with attention to detail.

Tips To Advance A Career To Become A Machine Learning Expert

Machine learning experts start at a junior position and become an expert with professional experience. The years of experience help strengthen existing skills and develop new ones. Here are some tips to advance your career as a machine learning expert:

Gain expertise on the latest machine and deep learning technologies by working on several types of projects
Contribute to team projects and collaborate with people
Work with cross-functional teams and take on leadership roles
Follow industry trends in the machine and deep learning technologies
Learn new skills that help improve your performance and contribute to the work
Mentor junior colleagues and develop new systems to guide them

Please note that none of the companies, institutions or organisations mentioned in this article are associated with Indeed.

Salary figures reflect data listed on Indeed Salaries at time of writing. Salaries may vary depending on the hiring organisation and a candidate's experience, academic background and location.