Over the last few years, artificial intelligence (AI) has opened up possibilities for the future. From space exploration to melanoma detection, 카지노사이트 it is making waves across industries, making impossible things possible.
As a result, there has also been a steady growth in AI careers—LinkedIn puts artificial intelligence practitioners among the ‘jobs on the rise’ in 2021. In this blog post, we explore the ten awesome and high-paying AI careers you can pursue in 2021 and beyond.
Is Artificial Intelligence a Good Career?
- AI jobs are plenty, hiring growing by 32% in the last couple of years
- There is a high talent gap—not enough qualified applicants for vacant positions
- AI professionals earn top salaries, well north of $100,000
- As a rapidly evolving industry, growth opportunities in AI careers are diverse
- AI careers are flexible—you could be a freelancer, consultant, researcher, practitioner, or even build your own AI products
What’s the Current AI Job Outlook?
The current AI job outlook is quite promising. The US Bureau of Labor Statistics expects computer science and information technology employment to grow 11% from 2019 to 2029. This will add about 531,200 new jobs in the industry. This, it appears, is a conservative estimate. ‘AI and Machine Learning Specialists’ is the second on the list of jobs with increasing demand as per the World Economic Forum.
As the industry matures, jobs in AI will not only grow in number but also complexity and diversity. This will open doors for various professionals—junior, senior, researchers, statisticians, practitioners, experimental scientists, etc. The outlook for ethical AI is also looking up.
What AI Careers Can You Pursue?
Despite being a new and niche field, careers in artificial intelligence aren’t homogenous. Within AI, there are various kinds of jobs needing specific skills and experience. Let us look at the top ten one by one.
1. Machine Learning Engineer
Machine learning engineers 바카라사이트 are at the intersection of software engineering and data science. They leverage big data tools and programming frameworks to create production-ready scalable data science models that can handle terabytes of real-time data.
Machine learning engineer jobs are best for anyone with a background that combines data science, applied research, and software engineering. AI jobs seek applicants with strong mathematical skills, experience 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.
The average salary of a machine learning engineer in the US is $1,31,000. Organizations like Apple, Facebook, Twitter, etc., pay significantly higher—in the range of $170,000 to $200,000. Read more about ML engineer salaries here.
2. Data Scientist
Data scientists collect data, analyze it, and glean insights for a wide range of purposes. They use various technology tools, processes, and algorithms to extract knowledge from data and identify meaningful patterns. This could be as basic as identifying anomalies in time-series data or complex as predicting future events and making recommendations. The primary qualifications expected of a data scientist are:
- Advanced degree in statistics, mathematics, computer science, etc.
- Understanding of unstructured data and statistical analysis
- Experience with cloud tools like Amazon S3 and the Hadoop platform
- Programming skills with Python, Perl, Scala, SQL, etc.
- Working knowledge of Hive, Hadoop, MapReduce, Pig, Spark, etc.
3. Business Intelligence Developer
Business intelligence (BI) developers process complex internal and external data to identify trends. For instance, in a financial services company, this could be someone monitoring stock market data to help make investment decisions. In a product company, this could be someone monitoring sales trends to inform distribution strategy.
However, unlike a data analyst, business intelligence developers don’t create the reports themselves. They are typically responsible for designing, modeling, and maintaining complex data in highly accessible cloud-based data platforms for business users to use the dashboards. 온라인카지 The qualifications expected of a BI developer are:
- Bachelor’s degree in engineering, computer science, or a related field
- Hands-on experience in data warehouse design, data mining, SQL, etc.
- Familiarity with BI technologies like Tableau, Power BI, etc.
- Strong technical and analytical skills
Business intelligence developers earn an average salary of $86,500, going up to $130,000 with experience.
4. Research Scientist
The research scientist role is one of the most academically-driven AI careers. They ask new and creative questions to be answered by AI. They are experts in multiple disciplines in artificial intelligence, including mathematics, machine learning, deep learning, and statistics. Like data scientists, researchers are expected to have a doctoral degree in computer science.
Hiring organizations expect research scientists to have extensive knowledge and experience in computer perception, graphical models, reinforcement learning, and natural language processing. Knowledge of benchmarking, parallel computing, distributed computing, machine learning, and artificial intelligence are a plus.
Research scientists are in high demand and command an average salary of $99,800.
5. Big Data Engineer/Architect
Big data engineers and architects develop ecosystems that enable various business verticals and technologies to communicate effectively. Compared to data scientists, this role can feel more involved, as big data engineers and architects typically are tasked with planning, designing, and developing big data environments on Hadoop and Spark systems.
Most companies prefer professionals with a Ph.D. in mathematics, computer science, or related fields. However, as a more practical role than that of, say, a research scientist, hands-on experience is often treated as a good substitute for a lack of advanced degrees. Big data engineers are expected to have programming skills in C++, Java, Python, or Scala. They also need to have experience in data mining, data visualization, and data migration.
Big data engineers are among the best-paid roles in artificial intelligence, with an average salary of $151,300.
6. Software Engineer
AI software engineers build software products for AI applications. They bring together development tasks like writing code, continuous integration, quality control, API management, etc., for AI tasks. They develop and maintain the software that data scientists and architects use. They stay informed and updated about new artificial intelligence technologies.
An AI software engineer is expected to be skilled in software engineering and artificial intelligence. They need to have programming skills as statistical/analytical skills. Companies typically look for a bachelor’s degree in computer science, engineering, physics, mathematics, or statistics. To land a job as an AI software engineer, certifications in AI or data science are helpful too.
The average salary of a software engineer is $108,000. This goes up to $150,000 based on your specialization, experience, and industry.
7. Software Architect
Software architects design and maintain systems, tools, platforms, and technical standards. AI software architects do this for artificial intelligence technology. They create and maintain AI architecture, plan and implement solutions, choose the toolkit, and ensure a smooth data flow.
AI-driven companies expect their software architects to have at least a bachelor’s degree in computer science, information systems, or software engineering. As a practical role, experience is as important as educational qualification. Hands-on experience with cloud platforms, data processes, software development, statistical analysis, etc., will place you in good stead.
Software architects earn an average salary of $150,000. Your salary can go up significantly with expertise in artificial intelligence, machine learning, and data science.
8. Data Analyst
For a long time, the data analyst was someone who collected, cleaned, processed and analyzed data to glean insights. For the most part, these used to be mundane, repetitive tasks. With the rise of AI, much of the mundane work has been automated. Therefore, the data analyst role has upgraded to join the new set of AI careers. Today, data analysts prepare data for machine learning models and build meaningful reports based on the results.
As a result, an AI data analyst needs to know more than just spreadsheets. They need to be skilled in:
- SQL and other database languages to extract/process data
- Python for cleansing and analysis
- Analytics dashboards and visualization tools like Tableau, PowerBI, etc.
- Business intelligence to understand the market and organizational context
A data analyst earns an average salary of $65,000. However, high-technology companies like Facebook, Google, etc., pay in excess of $100,000 for data analyst roles.
9. Robotics Engineer
The robotics engineer is perhaps one of the first of AI careers, when industrial robots were gaining popularity as early as the 1950s. From the assembly lines to teaching English, robotics has come a long way. Healthcare uses robot-assisted surgeries. Humanoid robots are being built to be personal assistants. A robotics engineer’s job is to make all this and more happen.
Robotics engineers build and maintain AI-powered robots. For such roles, organizations typically expect advanced degrees in engineering, computer science, or similar. In addition to machine learning and AI qualifications, robotics engineers might also be expected to understand CAD/CAM, 2D/3D vision systems, the Internet of Things (IoT), etc.
The average salary of a robotics engineer is $87,000, which can go up to $130,000 with experience and specialization.
10. NLP Engineer
Natural Language Processing (NLP) engineers are AI professionals who specialize in human language, including spoken and written information. The engineers who work on voice assistants, speech recognition, document processing, etc., use NLP technology. For the role of an NLP engineer, organizations expect a specialized degree in computational linguistics. They might also be willing to consider applicants with a qualification in computer science, mathematics, or statistics.
In addition to general statistical analysis and computational skills, an NLP engineer would need skills in semantic extraction techniques, data structures, modeling, n-grams, a bag of words, sentiment analysis, etc. Experience with Python, ElasticSearch, web development, etc., could be helpful.
The average salary of an NLP engineer is $78,000, going up to over $100,000 with experience.