Is AI a Good Career?
Artificial Intelligence (AI) is regarded a potential career path owing to its huge employment growth, with hiring rising by 32% in recent years, and a large talent gap suggesting a strong need for competent workers. AI positions, including engineers, researchers, and experts in natural language processing, attract significant wages, average over $100,000, indicating the industry’s significance and potential for financial gain.
The industry provides numerous development options and flexibility, enabling experts to operate in various roles such as freelancers, consultants, or product developers. Moreover, the abilities obtained in AI are transferable across different sectors, making it a flexible and desirable employment option.
Become a Data Scientist. LaData Scientistur Money Back.
Build job-ready skills with 28 mini-projects, three capstones, and an advanced specialty project. Work 1:1 with an industry mentor. Land a job — or your money back.
AI Jobs & Careers
Despite being a young and specialist industry, professions in artificial intelligence aren’t uniform. Within AI, there are numerous sorts of occupations demanding certain abilities and expertise.
Machine Learning Engineer
Experts in deep learning, machine learning, and programming develop scalable data models for analyzing enormous volumes of data; these professionals work at tEngineer for Softwarescience and software engineering.
$131 thousand
Data Scientist
Experts in turning unstructured data into meaningful patterns use technology and algorithms for analysis; they need graduate degrees and proficiency with staData Scientist and programming.
$105 thousand
Developer of Business Intelligence
BI developers create and manage data platforms for dashboards. They are proficient in processing and analyzing data to identify patterns; they also need to have a foundation in computer science or engineering and knowledge of data warehouse architecture and BI technologies.
$87,000.
Scientist for Research
These individuals are passionate about using creative questions to advance artificial intelligence. They excel in statistics, mathematics, machine learning, andInstruments learning. They often have doctorates and have experience in computer vision and natural language processing.
$100,000.
Big Data Architect/Engineer
Prioritize developing systems that enable communication between various technologies and business domains. These systems frequently involve working with Hadoop and Spark systems and call for programming, data mining, and visualization skills. Practical experience is highly valued in addition to or instead of advanced degrees.
$151,001
Software Engineer
focus on developing software for artificial intelligence (AI) applications, combining development duties with AI-specific requirements like API management and continuous integration. TheEngineer for Softwareed in programming and analysis as well as software engineering, and they should have an appropriate bachelor’s degree and certifications in data science or AI.
$108 thousand
Program Developer
Concentrate on the development and upkeep of artificial intelligence-specific systems and platforms. These require a combination of formal education and real-world experience in fields like cloud computing and data processing, with a focus on AI, machine learning, and data science to maximize their value.
$150,000.
Analyst of Data
Modern analysts need to be proficient in Python, SQL, analytics dashboards, and business intelligence in addition to being able to prepare data for machine learning models and produce insightful reports.
$65 thousand
Engineer for Robotics
Advanced degrees and expertise in fields like CAD/CAM, machine learning, artificial intelligence (AI), and the Internet of Things (IoT) are prerequisites for robotics engineers, who create and manage AI-powered robots.
$87,000.
NLP Specialist
Specializing in human language technology, NLP engineers work on developing voice assistants, speech recognitioEngineer for Roboticsrocessing systems, requiring expertise in computational linguistics or related fields, along with skills in semantic extraction, data modeling, and programming languages like Python.
$78,000.
Machine Learning Engineer
Data science and soNLP Specialisteering meet at the intersection of machine learning engineers. They employ big data technologies and programming frameworks to construct production-ready scalable data science models that can manage terabytes of real-time data.
Machine learning engineer positions are appropriate for someone with a background that combines data science, applied research, and software engineering. AI jobs need people with excellent mathematical abilities, expertise in machine learning, deep learning, neural networks, and cloud applications, and programming skills in Java, Python, and Scala. It also helps to be well-versed in software development IDE tools like Eclipse and IntelliJ. You will probably require a baca bachelor’s degreeomputer Science or a similar subject.
The average income of a machine learning engineer in the US is $​​131,000. Organizations like Apple, Facebook, Twitter, etc., pay substantially higher—in the typical wage range of $170,000 to $200,000. Read more about ML engineer wages here.
Data Scientist
Data scientists take raw data, evaluate it, and derive insights for a broad variety of reasons. They employ diverse technological tools, procedures, and algorithms to extract information from data and uncover significant patterns. This might be as simple as seeing irregularities in time-series data or as intricate as forecasting the future and offering advice. The following are the main requirements for a data scientist:
- A bachelor’s degree
- advanced degree in computer science, mathematics, statistics, etc.
- Recognizing unstructured data and doing statistical analysis
- familiarity with cloud resources such as Hadoop and Amazon S3
- ability to program in Python, Perl, Scala, SQL, etc.
- working familiarity with MapReduce, Pig, Spark, Hadoop, Hive, etc.
$105,000 is the average income for a data scientist. A director of data science post may pay up to $200,000 on average with expertise.
Developer of Business Intelligence
To find patterns, business intelligence (BI) engineers analyze intricate internal and external data. An example of this would be someone who keeps an eye on stock market data to assist in investment decision-making in a financial services organization. This may be a person in a product firm who keeps an eye on sales patterns to guide distribution strategy.
Business intelligence developers, however, do not write the reports themselves, in contrast to analysts. In order for business users to utilize the dashboards, they are usually in charge of developing, modeling, and managing complicated data on highly accessible cloud-based data platforms. The following credentials are anticipated of a BI developer:
- A bachelor’s degree in computer science, engineering, or a similar discipline
- practical knowledge of SQL, data mining, data warehouse architecture, etc.
- knowledge of BI tools such as Tableau, Power BI, etc.
- strong analytical and technical abilities
The average pay for business intelligence developers is $86,500, but with expertise, this may reach $130,000.
Scientist for Research
One of the AI jobs with the highest academic demands is research scientist. They provide original and imaginative queries for AI to respond to. They are specialists in a variety of artificial intelligence fields, including as statistics, machine learning, deep learning, and mathematics. Researchers are required to have a doctorate in computer science, much like data scientists.
Employing companies want for research scientists with deep expertise in natural language processing, graphical modeling, reinforcement learning, and computer perception. It is advantageous to have knowledge in artificial intelligence, machine learning, distributed computing, benchmarking, and parallel and parallel computing.
The average income for research scientists is $99,800, however this might fluctuate due to their high demand.
Big Data Architect/Engineer
Big data engineers and architects create ecosystems that provide successful communication across different business verticals and technology. This profession might seem more extensive than that of a data scientist since engineers and architects are usually responsible for the planning, building, and development of big data environments on Hadoop and Spark platforms.
Professionals with a Ph.D. in computer science, mathematics, or similar subjects are preferred by most employers. Nonetheless, practical experience is sometimes seen as a decent stand-in for a lack of advanced degrees, since it is more relevant to this profession than, example, that of a research scientist or AI engineer. It is required of big data engineers to be proficient in C++, Java, Python, or Scala programming. Additionally, they must have prior expertise with data transfer, data mining, and data visualization.
With an average pay of $151,300, big data engineers are among the highest paid positions in artificial intelligence. However, your typical pay may differ depending on the industry.
Software Engineer
Software products for AI applications are created by AI software developers. For AI jobs, they combine development duties such as code authoring, quality control, continuous integration, API administration, etc. They create and manage the software used by architects and data scientists. They keep up with the latest developments in artificial intelligence technology.
Proficiency in both software engineering and artificial intelligence is anticipated of an AI software engineer. They need statistical and analytical abilities in addition to programming abilities. Bachelor’s degrees in computer science, engineering, physics, mathematics, or statistics are usually required by employers. Certifications in data science or AI are also beneficial in securing employment as an AI software developer.
$108,000 is the average compensation for a software engineer. Depending on your sector, experience, and area of expertise, this may increase to an average compensation of $150,000.
Program Developer
Systems, platforms, tools, and technical standards are all designed and maintained by software architects. This is what artificial intelligence software architects do for technology. They design and manage AI architectures, organize and carry out solutions, choose the appropriate toolset, and guarantee efficient data flow.
Software architects are expected to have a bachelor’s degree in computer science, information systems, or software engineering by AI-driven businesses. Experience is just as vital in a practical function as education. You will be well-served by having practical expertise with cloud platforms, data processing, software development, statistical analysis, etc.
The average compensation for software architects is $150,000. Proficiency in data science, machine learning, and artificial intelligence may greatly increase your average wage.
Analyst of Data
A data analyst used to be someone who gathered, cleaned, processed, and examined data in order to extract insights. These were mostly routine, repetitive jobs in the past. A large portion of routine labor has been mechanized as AI has grown. As a result, the analyst position has been upgraded to include the new AI professions. These days, data analysts prepare data for models of machine learning and create insightful reports based on the findings.
An AI data analyst must therefore be knowledgeable about more than just spreadsheets. They need to be proficient in:
- Using SQL and other database languages to handle and extract data
- Python for cleaning and analysis
- tools for data visualization and analytics, such as Tableau, PowerBI, etc.
- Using business analytics to comprehend the organizational and market environment
The average compensation for a data analyst is $65,000. However, high-technology businesses like Facebook, Google, etc., pay in excess of $100,000 average wage for data analyst jobs.
Robotics Engineer
The robotics engineer is possibly one of the earliest of AI vocations, when industrial robots began gaining popularity as early as the 1950s. From the assembly lines to teaching English, robots has gone a long way. Healthcare employs robot-assisted procedures. Humanoid robots are being designed to be personal assistants. A robotics engineer’s job is to make all this and more happen.
Robotics engineers construct and maintain AI-powered robots. Organizations usually need graduate degrees in computer science, engineering, or a related field for such employment. Robotics engineers may also be required to have knowledge of CAD/CAM, 2D/3D vision systems, the Internet of Things (IoT), and machine learning and artificial intelligence.
The typical pay for a robotics engineer is $87,000, but with specialization and experience, this may rise to an average of $130,000.
NLP Engineer
AI experts with a focus on spoken and written human language are known as natural language processing (NLP) engineers. NLP technology is used by engineers who work on voice assistants, speech recognition, document processing, etc. Organizations need a specific degree in computational linguistics for the position of NLP engineer. Candidates having a background in statistics, mathematics, or computer science may also be given consideration.
An NLP engineer would need expertise in modeling, data structures, sentiment analysis, n-grams, a bag of words, semantic extraction methods, and general statistical analysis in addition to computing abilities. It might assist if you have any experience with Python, ElasticSearch, web development, etc.
An NLP engineer typically makes $78,000, but with expertise, that compensation may rise to over $100,000.
What Qualifications Are Required for Entry-Level AI Jobs?
Even though no two AI jobs are the same, there are some qualifications that are universal for entry-level roles. We requested ChatGPT to scan a set of AI jobs from firms like OpenAI and Honda and provide a list of the most often identified elements in order to assist better understand what skillsGeneral Conditionsriteria are shared across job advertisements.
These are the findings:
Competencies and Information
- comprehension of the algorithms and ideas of AI/ML.
- outstanding ability to analyze and solve problems.
- proficiency in programming languages, preferably Python; R or Java may also be necessary.
- familiarity with machine learning frameworks like PyTorch, TensorFlow, and Keras.
- familiarity with tools for data analysis and manipulation (SQL, Pandas, NumPy).
- familiarity with distributed computing frameworks and big data technologies (e.g., Hadoop, Spark).
- expertise in the creation and analysis of scientific software.
- Capacity to explain technical ideas to stakeholders who are not technical.
- a keen eye for detail and the capacity handle complicated data.
- It is advantageous to have experience in computer vision, natural language processing (NLP), or other AI-related domains.
- familiarity with AWS SageMaker and Azure Machine Learning, two cloud-based machine learning technologies.
Tools
- Frameworks for machine learning: PyTorch, Keras, and TensorFlow.
- SQL, Pandas, and NumPy for data analysis.
- Technologies for Big Data: Spark, Hadoop.
- Cloud platforms include Azure Machine Learning and AWS SageMaker.
- Development Tools: GitHub for ML Operations, Jupyter Notebook.
- Tableau and PowerBI are two BI tools (for delivering data insights).
General Requirements
- a bachelor’s degree in engineering, computer science, physics, mathematics, or a similar technological discipline. For highly specialized positions, further degrees (Master’s, Ph.D.) are desired.
- one to three years of expertise in a machine learning or artificial intelligence capacity.
- exceptional communication abilities both in writing and speaking.
- zeal for creating solutions to challenging technical issues.
- the capacity to work well in cross-functional teams.
- adherence to moral and legal requirements including model bias, security, and data privacy.
Although the aforementioned is by no means an exhaustive list, it serves as a useful checklist for prospective AI experts to ensure they have covered the fundamentals.
Which Sectors Are Employing AI Experts?
Today, LinkedIn has over 15,000 AI job listings. Numerous sectors’ worth of organizations are recruiting. Technology seems to have the greatest number of open AI jobs; organizations such as Apple, Microsoft, Google, Facebook, Adobe, IBM, Intel, and so on are hiring for AI positions.
Consulting majors like PWC, KPMG, Accenture, etc. closely follow this. GlaxoSmithKline has several open AI-related positions, indicating that healthcare organizations are hiring more people. Media firms like Warner and Bloomberg, as well as retailers like Walmart and Amazon, are also hiring.
FAQs Regarding AI Careers
Are There Many Jobs in AI?
The employment prospects for artificial intelligence (AI) is now quite bright. Employment in computer science and information technology is predicted by the US Bureau of Labor Statistics to increase by 11% between 2019 and 2029. As a result, the sector will gain over 531,200 new employment, with salaries that are higher than average to entice workers.
Is It Possible to Enter AI Without Experience?
The capacity to complete tasks is what distinguishes an AI professional in the real world. Experience is the sole source for this. Thus, even if it’s not quite corporate work experience, you still need to have practical experience to get a position in AI. For example, Springboard’s Data Science Career Track offers 14 practical projects to help you get experience using AI to solve business problems.
Does Employment in Artificial Intelligence Require a Degree?
Most job postings online will require at least a bachelor’s degree. However, as we indicated above, the skill gap is rising. Organizations may no longer reject individuals without a college degree if they have verifiable talents and expertise in artificial intelligence.
Do You Need an Advanced Degree (Master’s Degree) to Work in AI?
You don’t have need a Master’s Degree, but even entry level positions may demand a Bachelor’s Degree in Computer Science or Information Technology, or any other engineering degree. Examine the necessary abilities carefully while applying for entry-level jobs. Do you truly need a master’s degree to pursue this position, or do you already possess the necessary abilities and knowledge? One may operate in the profession without additional education if they possess the necessary technical capabilities, communication abilities, and problem-solving abilities, as well as a portfolio to support their claims.
