Machine learning is the future. And India is taking the forefront in leveraging this state-of-the-art technology big time. With a projected annual growth rate of 30% from 2021 to 2025, the Indian machine-learning market is exploding. Likewise, the demand for machine learning experts is rising, and businesses are ready to pay a lucrative package for skilled professionals. Top machine learning jobs usually carry a generous 6-figure package.
But there is a catch – a shortage of skilled professionals. There will be over 200,000 unfilled jobs by 2025. If you are trying to make it in the industry, you need to pick up relevant skills. Learning programming languages like Python, mastering statistics and machine learning concepts, honing data analysis abilities, and developing problem-solving skills are crucial.
The blog sheds light on the top ML jobs and how to build a robust career in machine learning.

Growing Demand for Machine Learning Experts

Machine learning has swiftly become one of the biggest game changers for industries. From healthcare to banking and finance, e-commerce, and technology, machine learning is changing the way companies operate.
The adoption of machine learning in industries has pushed the demand for skilled professionals. The high demand for machine learning professionals has resulted in attractive salary packages across the industry.

Supply gap pushing the pay scale

According to industry reports, machine learning engineers can range from ₹ 3.0 Lakhs to ₹ 20.0 Lakhs or more. Not surprisingly, AI research scientists and specialists often earn higher salaries, due to their advanced skill set and expertise.
India is currently going through an acute ML talent crunch. As per market sources, there are more than 50K open AI and machine learning jobs available in India. However, employers are struggling to find the right talents for their requirements. This demand and supply gap has pushed the pay scale to a new height. Today an ML engineer in India can earn up to ₹9,50,000 per year at the start of their career with a 13% to 16% annual increment.

Top Machine Learning Jobs

Machine Learning Engineer

This is one of the most in-demand machine learning jobs for freshers. ML engineers are responsible for designing, building, and deploying ML systems and models. Part of their job role also includes data gathering, cleaning, and preprocessing for training ML models.


Director of Analytics

The Analytics Director shoulders the responsibility of mentoring data warehousing and data analytics teams. They also delve into leadership roles and strategic decision-making for business organisations.


NLP Specialist

NLP Experts develop and implement models that allow seamless interaction between human language and computers. They deploy deep learning and machine learning techniques to develop advanced systems for text summarisation, sentiment analysis, speech recognition, and more.


Data Scientist

Data Scientists gather, analyse, as well as interpret massive volumes of complicated data sets to extract actionable insights. They follow a multi-disciplinary approach that involves mathematics, statistics, computational, and machine learning techniques.


Algorithm Engineer

Algorithm Engineers design, implement, as well as optimise computer algorithms. In other words, they enhance AI applications that help to detect issues or patterns in huge data sets.

Roadmap to Build Career in Machine Learning

Machine learning is a vast domain. You will need a combination of technical expertise, leadership qualities, and domain knowledge. Most employers are seeking candidates with a strong foundation in machine learning algorithms, data modelling, and statistical analysis. Proficiency in programming languages such as Python, R, or Java is often a prerequisite. Additionally, experience with popular machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn is highly valued.
A career in Machine Learning is undoubtedly rewarding. Here is a curated roadmap to launch and build a thriving career in the ML domain.

1. Identify Your Niche: Machine learning is a vast field with various domains like natural language processing (NLP), computer vision, reinforcement learning, etc. Identify your interests and strengths to choose the most suitable domain to specialise in.


2. Online Courses and Certifications: You will find both online and offline academic platforms for machine learning certification course programs. Sign up with a course that offers live interactive class sessions with industry experts such as the one provided by DataSpace Academy.
   Eligibility Criteria:-
   • Bachelor’s Degree with Science and/or Programming, and/or Tech background
   • Professionals with experience in the data domain
   • Learners with a Diploma (10+2+3) with a Science and/or Tech background


3. Workshops and Bootcamps: Attend machine learning workshops and boot camps to gain focused and intensive training in specific areas of interest. Bootcamps offer excellent learning courses to provide the necessary knowledge and skills for success in a particular arena.


4. Hands-on Projects: Hands-on experience is crucial for landing rewarding machine learning job opportunities. Work on personal projects, join internships, or participate in Kaggle competitions to gain relevant experience. Also, contributing or collaborating on open-source machine learning projects will help you to learn from experienced developers and build a strong network in the community.

Wrapping Up

The global machine-learning market is expected to reach $188.34 billion by 2030, and the demand for machine-learning professionals is only going to grow in the years to come.
However, also remember, Machine Learning is a rapidly evolving field. Dedicate your time to update your knowledge and skills to keep up with the latest trends and technologies. Attend workshops, conferences, and webinars. Stay updated with new libraries, tools, and techniques. The more you invest in continuous learning, the more adaptable and valuable you become as a machine learning professional.