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Surjani Dutta
Surjani Dutta

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How to become an AI engineer in 2024?

Artificial Intelligence (AI) engineering has emerged as the most promising and dynamic career path in technology. AI is the branch of computer science that focuses on creating intelligent machines capable of simulating human-like behavior. Witnessing the rapid advancements in various industries, the demand for skilled AI engineers continues to escalate. AI engineers are responsible for designing, developing, and deploying AI-based systems across various domains, including healthcare, finance, automotive, and more.

But what does it take to embark on a career in AI engineering? Is it a viable option for aspiring technologists?
Let's delve into the world of AI engineering and explore the opportunities and requirements for aspiring professionals

Is AI Engineering A Good Career Option?

In a word, yes. AI engineering offers opportunities for individuals passionate about cutting-edge technology and innovation. With AI permeating almost every aspect of modern life, from virtual assistants to autonomous vehicles, the demand for AI engineers is at an all-time high.
According to industry reports, the global AI market is projected to reach billions of dollars in the coming years, creating a wealth of job opportunities for skilled professionals.
Moreover, AI engineering offers a dynamic and intellectually stimulating career path, allowing individuals to work on groundbreaking projects and contribute to transformative innovations.

What Skills Required For AI Engineering?

Becoming a successful AI engineer requires a diverse skill set. Here are some essential skills for aspiring AI engineers:v
Programming Proficiency: Strong proficiency in programming languages such as Python, R, Java, or C++ is essential for AI engineering. Familiarity with frameworks like TensorFlow and PyTorch is also beneficial.
Mathematical Aptitude: A solid foundation in mathematics, including calculus, linear algebra, probability, and statistics, is crucial for understanding and developing AI algorithms.
Machine Learning Mastery: It is necessary to know machine learning principles, methods, and frameworks like TensorFlow and PyTorch. Building reliable AI models requires an understanding of regression, classification, clustering, supervised and unsupervised learning, and categorization.
Data Analysis Skills: Proficiency in data analysis techniques, data preprocessing, feature engineering, and model evaluation is necessary for working with large datasets and extracting valuable insights.
Problem-solving Abilities: To recognize and address complicated problems in AI development, AI engineers require excellent analytical and problem-solving skills. In this sector, the ability to think critically and tackle challenges creatively is essential.
Deep Analysis: Deep learning approaches, such as neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial networks (GAN), should be of specialization for AI developers. Deep learning can be implemented with the help of programs like TensorFlow and Keras.
Natural Language Processing (NLP): Natural language processing (NLP) is the area of artificial intelligence that studies language use in human-computer communication. AI engineers benefit from having a solid understanding of NLP fundamentals including named entity identification, text categorization, and sentiment analysis.

Steps To Become An AI Engineer

1. Get a Diploma in Secondary Education

The first requirement to be met to pursue a career in artificial intelligence engineering is obtaining a high school diploma with a concentration in one of the scientific subjects, such as mathematics, physics, or chemistry. Statistics is another one of the core subjects you can study in school. You'll have a good basis for your future learning if you graduate from high school with a strong knowledge of science topics.

2. Finish Bachelor's Degree

An alternative to a four-year Bachelor of Technology (B.Tech) program is to enroll in a three-year Bachelor of Science (B.Sc.) program. Another option is to major in artificial intelligence alongside data science and machine learning after receiving an engineering degree in a theoretically similar discipline, such as computer science or information technology. You might need to perform well on the Joint Entrance Examination (JEE) to gain admission to esteemed engineering colleges like NITs, IITs, and IIITs.

3. Get A Master's Degree (optional)

Obtaining an Artificial Intelligence Engineer Master's degree in a related field may help you stand out from the competition for AI engineering jobs and boost your income potential. It could provide you with specialized technical skills in addition to a thorough comprehension of the subject.

4. Develop Programming Skills

Gain expertise in programming languages like R, Python, Java, and C++. To improve your programming skills, practice putting algorithms into practice and working through coding challenges.

5. Learn Stats and Maths

Build a strong foundation in mathematics, including statistics, probability theory, calculus, and linear algebra. Investigate subjects including mathematical modeling, numerical techniques, and optimization.

6. Get Deep Into Deep Learning

Investigate the area of deep learning, which is centered on sophisticated machine learning methods and neural networks. Recognize terms like generative adversarial networks (GAN), recurrent neural networks (RNN), convolutional neural networks (CNN), and artificial neural networks. By employing well-known frameworks like TensorFlow or PyTorch to create deep learning models, you can obtain practical experience.

7. Master NLP Processing

Learn about Natural Language Processing (NLP), the field that studies natural language-based human-computer interaction. The study named entity identification, text categorization, sentiment analysis, and language production methods.
Working on NLP projects with libraries like NLTK or spaCy will give you real-world experience.

8. Explore Machine Learning

Learn about the principles and techniques of machine learning (ML). Study about evaluation metrics, regression, classification, clustering, supervised learning, and unsupervised learning. Engage in real-world experience by working with datasets and ML projects.

9. Acquire Certifications

Conversely, enrolling in certificate programs or artificial intelligence courses might help you improve your skills for less money. You can study graduate-level and post-graduate-level degrees in machine learning and artificial intelligence.

10. Build Real-World Experience

It's crucial to gain real-world experience to become an AI engineer. Although a solid background in computer science, statistics, and mathematics is necessary, practical problem-solving experience is just as vital. You can obtain expertise with a range of tools and technologies utilized in the field of AI engineering by working on projects and taking part in hackathons. Online programs and boot camps can also offer mentorship and structured learning, allowing you to work on real projects and get input from specialists in the field. You can advance the field of artificial intelligence and become a proficient AI engineer by combining your academic knowledge with real-world experience.

11. Specialize and Focus

Identify your areas of interest within AI engineering, such as machine learning, computer vision, natural language processing, or robotics, and specialize accordingly. Dive deep into your chosen domain, explore advanced concepts, and stay updated with the latest developments and trends.

12. Continuous Learning and Growth

AI engineering is a rapidly evolving field, so commit to lifelong learning and professional development. Stay updated with the latest research papers, attend conferences and workshops, and pursue advanced certifications to stay ahead of the curve.

Qualifications Needed In AI Engineering

In AI engineering, a strong educational background in computer science, mathematics, or a related discipline is highly recommended. Most AI engineering roles require a bachelor's or master's degree, preferably with coursework or specialization in artificial intelligence, machine learning, data science, or a related field. Additionally, certifications or training programs in AI and machine learning can enhance your qualifications and make you more competitive in the job market.

Responsibilities of an AI Engineer

First thing first, carry out certain duties as an AI or ML engineer, like creating, testing, and implementing AI models with programming methods like logistic regression, random forest, linear regression, and more.
Among the duties are:

  • Create application program interfaces (APIs) from the machine learning models so that other applications can utilize them.
  • Create AI models from the ground up and assist stakeholders and product managers in understanding the benefits the model brings to their respective roles within the company.
  • Construct infrastructure for data transformation and ingestion.
  • Automate the data science team's infrastructure.
  • Conduct statistical analysis and fine-tune the outcomes to enable the organization to make more informed choices.
  • Establish and oversee the infrastructure for AI development and products.
  • Play well with others, as cooperation is essential.

Salary Expectations In AI Engineering

The salary expectations for AI engineers vary depending on factors such as experience, education, location, industry, and company size. According to industry reports, the average salary range for AI engineers is given below-
Entry-level AI Engineer: If you're a recent graduate or have little experience, you should be prepared to pay between INR 6 lakhs and INR 10 lakhs a year. Depending on your performance and the organization's reputation, your income may rise.
Mid-level AI Engineer: You can make between INR 10 lakhs and INR 20 lakhs a year with three to five years of experience. At this point, the majority of your income is determined by your talents and knowledge.
Senior-level AI Engineer: Salary ranges for AI engineers with six years of experience and up are INR 20 lakhs to INR 40 lakhs annually. You could be able to work on innovative projects or assume leadership positions as a senior AI engineer.


Embarking on the journey to becoming an AI engineer requires dedication, perseverance, and a passion for innovation. By acquiring the necessary skills, education, and practical experience, you can position yourself for success in this dynamic and rewarding field. Whether you're a recent graduate or a seasoned professional looking to transition into AI engineering, the opportunities are endless. So, embrace the challenges, stay curious and committed to continuous learning, and let your passion for AI drive you toward a fulfilling and prosperous career in 2024 and beyond.

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