A Complete Guide To Strengthen Your Career as an AI Engineer- Fact Sheet
Goodbye 2019, an agony of suspense for AI. Hello 2020, we see a fascinating year ahead!
The science fiction of yesteryear is becoming a reality today. Chatbots and digital assistants are everywhere.
Thanks to the advent of artificial intelligence.
Currently, AI is one of the fastest-growing technology in the current job market, the demand for AI professionals outpaces the current skilled AI engineers.
Based on a study made by “Pew Research study on Future Jobs,”
It predicts AI to pervade human lives by 2025, eliminating every job possible. However, at the same time there, will be newer job opportunities for those having the right and relevant skillset.
Do you have what it takes to grab an AI job today?
Before we delve deeper, let us first understand what is AI engineering and who is an AI engineer?
· AI engineering
The term AI engineering simply refers to AI engineers who can conduct work on AI and machine learning with the help of algorithms.
· AI engineer
As an AI engineer, you will be completely engaged in a whole range of processes that include data preparation. In simple terms, once the individual finishes data preparation and manipulation, they need to engage themselves in constructing models for machine learning for the optimization of algorithms that already exist.
👉Demand and job prospects for AI in 2020
2020 is an open book for all professionals engaged in AI.
- By 2025, the AI market is projected to become USD 190 billion industry, predicts a research firm MarketsandMarkets
- According to IDC, the global spending made on AI systems to reach USD 57.6 billion by 2021
- 75% of commercial enterprises apps will be using AI by 2021, predicts IDC.
Job prospects: -
- AI is bound to create 2.4 million jobs this year says, Gartner.
- By 2021, AI augmentation is set to generate nearly USD 2.9 trillion in accelerating business value and as well as recover 6.2 billion hours of a worker’s productivity, a report by Gartner.
- In 2020, nearly 30% of all the B2B companies will be employing AI to accelerate at least one of their sales processes, prediction by Gartner.
- AI to revolutionize the marketing industry by 2020 says 80% of the B2B marketing executives, a report by Demandbase, a leader in Account-Based Marketing (ABM).
Here are the top emerging jobs worth grabbing in 2020 with their annual growth percentage, report based on LinkedIn: -
- Artificial intelligence specialist — 75%
- Robotics engineer — 40%
- Data scientist — 37%
- Data engineer — 33%
- Cyber security specialist — 30%
- Cloud engineer — 27%
👉But what does an AI engineer do — roles, responsibilities. What are they?
Many of you out there might know what is AI or perhaps know at least the definition of AI. However, there’s yet an unclear line that portrays and tells you what exactly an AI engineer does on their day to day activity.
Are you curious?
Well, certain things come in mind when we think of an AI engineer. However, the job profile depends upon the level of expertise an AI engineer holds.
However, in general, these are the roles and responsibilities they require to do:
- Development of machine learning applications based on requirements.
- Run machine learning tests and experiments and deploy them.
- Research, study and transform data science prototypes.
- Coordination with the data science team, robotics team, and the electric engineering team.
- Automating processes by making use of machine learning.
- Converting machine learning models into APIs so that other applications will be able to access them easily.
Here is an example of what they do daily: -
- AI engineers need to gather a large amount of data from HotJar users (a tool that reveals online behavior as well as the voice of the users). These data are then made to run against machine learning algorithms. Once this is done, common pitfalls and sources of user confusion are tracked, followed by analyzing the data and finding the pattern as to how and when the user confusion occurred.
- Model is then created combining both HotJar and A/B testing with the data procured from Google analytics and the information received from the on-cart abandonment. This is done to propose improved layouts resulting in an increased amount of time spent on that site or higher customer acquisition or perhaps other requirements specified by the business development team of the organization.
- The prediction needs to be clear owing to the success of these layouts made by the UX team. A machine learning algorithm is developed to take pictures of the website layouts that have been sketched by the UX team. This sketch will then be utilized by the software development team for finalized and finished layouts. Now when these layouts are finalized and the workflow implementation is done successfully, this will augment and speed up the feedback loop that is interfering with the website’s UX. Besides this, it can also save a lot of countless hours.
👉What is the career road map of an AI engineer?
Let’s start from the basics: -
- Earn a Bachelor’s degree in the following subjects
Going with the basics, an AI professional needs to have at least a degree in statistics, mathematics, calculus, algorithms, and probability.
Besides these earning a degree in the field of engineering, robotics, and physics is highly recommended. An easier way to start is by taking up a Bachelor’s degree in computer science.
2. Grab the technical skills required
- Programming skills such as Python, Perl, C/C++, Java
- Data science
- Statistics
- OOPS, modularity, and classes
- Software development
- Machine learning
- Neural networks
- Deep learning
- Robotics and electronics
Other skills include: -
- Utilization of modern software development techniques
- Coding skills at an advanced level
- Critical thinking
- Analytical thinking
- Creative thinking
- Techniques of software deployment in the production level
- Sense of taking the ownership of a project
These skills can either be acquired through practical implementation or either a Master’s degree in the field of computer engineering followed by a Ph.D. in an AI-related field.
3. Grab a Master’s degree
A Master’s degree is indispensable for every professional paving their AI career pathway. Since the job market is rapidly growing, earning a master’s degree is needed. A report by the U.S. Bureau of Labor Statistics, 18% of the jobs say they’ll need candidates with a Master’s degree by 2022.
Employees with a Master’s degree are considered to earn a considerably higher salary compensation as compared to those without these degrees.
Topics covered under the Master’s program include: -
- Social robotics
- Data mining
- AI and Society
- Evolutionary computing
- Knowledge representation
- Multi-agent systems
- Cognitive psychology
If you’re looking to become an AI-enabled professional in 2020 you must earn a certification since companies are quite agnostic with the AI techniques these days. You need to ensure you’re the right candidate for their company.
Opportunities in AI has moved beyond expectations, thus, instilling fear in the hearts of AI professionals who are already in the industry. Top employers are looking to hire AI researchers and AI specialists for different projects ranging from modeling risks to designing crop harvesting robots.
The hiring frenzy is affecting the current industry due to the shortage of talent. Earning a Ph.D. in AI will curb the skill-gap while also staying updated in the cutting-edge technology.
4. Prerequisites — job skills needed
Next comes acquiring the right set of skills to get into the AI industry. Here’s an important factor to note, becoming an AI engineer not only requires the candidate to be exceptionally great with their programming skills but they need to be great with their software development tools and techniques, both theoretically as well as practically.
Additionally, AI engineers and AI experts will need a solid understanding of software development that includes continuous delivery, continuous deployment (CI/CD), and continuous integration.
- They need to grasp solid approaches toward driving various testing practices — behavior-driven development and test-driven development.
- Extensive understanding of where machine learning can fit into the given continuous delivery pipelines as well as continuous integration. Simply put, AI professionals need to know how agile processes work in tech organizations. To get there, you’d probably need five to ten years down the line with your level of expertise in AI.
5. Certifications
According to Gartner, nearly 40% of customer-facing employees, as well as the government workers, will require to consult AI virtual support agents for making a decision or for process support to take place daily by 2022.
No doubt AI is gradually taking over the IT world, and earning an AI certification will only create an added value to your career. You can directly take up AI certification programs through credible online portals. With hiring becoming a challenge for most employers, being certified makes it much easier to get hired. Also, companies are giving top priority to candidates who’re certified in skills they’re looking to hire.
Earning a certification not only boosts your hiring potential but also increases your salary package between 13–25%.
6. Salary compensation
The salary compensation for AI engineers is impressive with AI job roles commanding six figures. A junior AI engineer earns near about USD 124,542 per annum while an average AI engineer makes around USD 171,715 per annum and a senior AI engineer earns around USD 257,530 per annum.
Putting aside all the misconceptions about robots and AI stealing away jobs, AI is here to save humanity and not take us to pitfalls.
👉Looking to chase your AI dreams, consider moving to these places today?
According to Indeed, a job site — there were 30,000 listings on this site while stressing their focus on 15 countries that were leading in AI.
Surprisingly, China leads the honor of being the first country that has the most job opportunities.
Top ten cities leading the AI bandwagon: -
1. Suzhou (China) — 3,329
2. Shanghai (China) — 1,624
3. Tokyo (Japan) — 1,258
4. Zhongshan (China) — 1,220
5. Ningbo (China) — 1,167
6. Beijing (China) — 1,129
7. Changsha (China) — 795
8. London (UK) — 744
9. New York (US) — 568
10. Bengaluru (India) — 566
Top Industries where AI engineers can revolutionize their career
Undoubtedly, the emergence of AI and machine learning has transformed the lives of many today including a few of the industries. From making better decisions to streamlining operations, AI has made its presence known today.
While AI is becoming a part of our daily lives these are the industries, sectors, and services that will soon be transformed by AI.
- DevOps
- Cloud hosting
- Cybersecurity
- Healthcare
- Manufacturing
- Retail
- Senior care
- City planning
- Construction
- Fashion
- Education
- Supply chain management
- Mental health diagnosis
Hungry for big bucks? Feast your eyes on AI career today!
