Artificial Intelligence is an amazing field. It is giving all the engineers an opportunity for next-level innovation. A huge amount of research has been done in the field and a lot can be done in the future.

These are the current profiles for AI Engineers

1. Data Scientist
2. Machine Learning Engineer
3. Computer Vision Engineer
4. Natural Language Processing Engineer
5. AI Engineer
6. Robotics Scientist
7. AI Product Manager
8. Big Data Engineer
9. Deep Learning Engineer

Let's understand these prospects in the field of AI, more particularly for engineers.

1 | Data Scientist

A data scientist is one who has a good command of Software Development and Statistics.

Engineers can opt for this profile if they have a good understanding of software development processes and statistical modeling. You start working with collecting data, do some experiments on it and gain insights, depending upon the insights from the data.

They should have a good understanding of programming languages like Python, SQL, and Scala.

Tools like Hadoop, Spark, or Hive.

In terms of education, engineers should have a master's degree in statistics, computer science, or AI/ML.

2 | Machine Learning Engineer

A machine learning engineer is one who has a good command of Mathematics, Data structure, and algorithms, development operations. He should be proficient in implementing an algorithm to code. Implementing new research papers to code.

Programming languages like Python, Java, Scala.

Frameworks like Scikit Learn.

Education, engineers should have a bachelor's or master's degree in computer science, AI/ML.

3 | Computer Vision Engineer

A computer vision engineer is one who has a good understanding of image processing, video processing and performs decision making through visuals. They also have a good command of machine learning algorithms.

Programming languages like Python, C, C++

Frameworks like OpenCV, YOLO.

Education, engineers should have a bachelor's or master's degree in computer science, AI/ML, Linear Algebra.

4 | Natual Language Processing Engineer

An NLP engineer is one who has a good understanding of human language, probability, advanced language models, and text analytics.

Programming languages like Python.

Frameworks like Gensim, Spacy, NLTK

Education, engineers should have a bachelor's or master's degree in computer science, AI/ML, Probability.

5 | AI Engineer

An AI engineer is one who solves complex problems using neural networks, handling AI infrastructures.

Programming languages like Python, Java.

Frameworks like Tensorflow, Keras.

Education, postgraduate degrees in the field of data science, computer science, or statistics are mandatory.

6 | Robotics Scientist

While robots prefer automation, some skilled builders should be involved. This minimizes the possibility of work cuts.

Education, engineers should have a Master in Robotics, Computing, or Engineering degree.

7 | AI Product Manager

An AI product manager is one who understands the end to the end product delivery. He knows how the AI is going to be implemented successfully to the user.

Should have a technical understanding of the technologies used in the product.

Good management skills.

Should estimate the business impact from the interpretation of data.

8 | Big Data Engineer

A big data engineer is one who build and administer big data of an organization and deals with preparing, managing and establishing a big data environment. The role is suitable for those who are keen to play with new technical tools and can step above the relational database box.

Programming languages like Python, R and Java.

Engineers who have a PhD in the field of Computer Science or Mathematics are given more preferences.

9 | Deep Learning Engineer

A Deep learning engineer is one who has a deep understanding of Computer Science fundamentals – data structures, algorithms, computability and complexity, and computer architecture.

Use mathematical formulas and techniques to perform complex computations and design advanced algorithms.

Programming language like Python, Java.

Frameworks like TensorFlow, Keras, Caffe, PyTorch.

Conclusion

According to the latest stats, the global Machine Learning market size that stood at US$ 6.9 billion in 2018, is projected to grow at a CAGR of 43.8% between 2019 to 2025. This will create so many jobs in the field of Artificial Intelligence and its sub fields.