The next big thing in tech is already here: artificial intelligence. To build a lucrative AI career now and in the future, you must begin by acquiring a strong understanding of the cognitive, philosophical, and logical foundations of AI research. Furthermore, you should be able to identify how cutting-edge AI programs can create intelligent solutions to solve complex problems. Let’s take a deeper dive.
Building your AI career
Industry verticals where AI job expertise is in high demand at present include:
Robotics
Areas of work include vision and planning, learning, motor control, linguistic communication, and cooperative behavior.
Informatics
Areas of work include AI applications for web crawling, email filtering, and data mining.
Marketing
Areas of work include the development of relevant, timely, and targeted marketing programs for new customer acquisition and reduction of existing customer attrition rates.
Engineering
Areas of work include intelligent control systems, fault diagnosis, intelligent design aids, intelligent production systems, integrated systems for manufacturing, sales, design, maintenance, and expert configuration tools
Medicine
Areas of work include diagnostics, interpretation of medical imaging, expert systems to support physicians, control and monitoring in ICUs, designing new drugs, and designing prosthetics.
Space
Areas of work include control and management of autonomous space vehicles and robots that are too far from earth to be manipulated directly by human beings on earth due to transmission delays, as well as planning and scheduling of automated space shuttle maintenance.
Defense is another major area where large fund allocations are being made for the use of artificial intelligence, leading to new job and career opportunities for AI experts.
Some of the positions in various industry verticals for AI personnel could require detailed background checks and security clearance procedures prior to hiring. This can depend on the sensitivity of the data and information that the employees are expected to handle.
Examples of typical AI career jobs
- Software developers and analysts
- AI engineers and scientists
- AI researchers and consultants
- Algorithm specialists
- Health-care professionals working with prosthetics, vision restoration devices, hearing aids, artificial organs
- Surgical technicians using robotic tools and instrumentation
- Aviation and military experts working with armaments, drones, and flight simulators
- Professors and teachers at trade and technical schools, universities, and vocational centers
Top AI career options and the required skills
If you are looking at potential career options in the field of artificial intelligence, consider these prime jobs as well as the skills that you will require to transition into these job roles.
Machine learning engineer
A machine learning engineer is one of the most sought-after jobs at present in the area of artificial intelligence. You must have the latest software skills, be capable of applying predictive models and use natural language processing as you work with massive data sets.
Furthermore, as a machine learning engineer, you will be expected to know the methodology of software development, Agile practices, and the full range of cutting-edge software development tools ranging from IDEs such as IntelliJ and Eclipse to the components of continuous deployment pipelines.
Qualifications
Companies looking to hire machine learning engineers prefer candidates who have a master’s or a doctoral degree in mathematics or computer science along with a working knowledge of current programming languages such as Java, Scala, and Python.
Professionals with good mathematical skills, expertise in computer programming, knowledge of computer languages and cloud applications, strong analytical and communication skills as well as certifications in machine learning usually have a solid chance to get hired by companies.
Robotic scientist
Although robots can automate various types of jobs, they need human programmers who work behind the scenes to monitor and control their accurate functioning. Robotic scientists are required to perform functions in multiple scientific fields ranging from security and healthcare to manufacturing and space exploration.
The key role of a robotic scientist is to develop automated mechanical devices that can perform specific tasks at human command. Other skills that are necessary for this role include developing computer programs and working in collaboration with other specialists to create prototypes.
Qualifications
A prerequisite for this job would be a bachelor’s degree in one of these fields of engineering: mechanical, electro-mechanical, electrical, or robotics.
Organizations also seek professionals with advanced specialization in physical sciences, mathematics, computer science, life sciences, CADD (computer-aided design and drafting), fluid dynamics, materials science, physics, and related certifications.
Data scientist
The job of a data scientist is to collect, interpret and analyze large amounts of data with the help of predictive analytics and machine learning to provide insights beyond the standard statistical analysis. A candidate for this job should have expertise in working with Big Data platforms and tools such as Pig, Hadoop, Spark, MapReduce, and Hive.
A data scientist should also be fluent in programming languages, such as Perl, Scala, Python, and SQL (structured query language), apart from statistical computing languages.
Qualifications
The candidate should hold a master’s or doctoral degree, and preferably an advanced degree or certification in computer science. Technical skills desirable for this job include a thorough knowledge of Python coding, SAS and R, Hadoop, and experience in using cloud tools such as Amazon’s S3. They should also have the ability to comprehend unstructured data.
Research scientist
Research scientists have expertise in multiple AI disciplines, such as machine learning, applied mathematics, and computational statistics. In particular, these fields of expertise include deep learning, reinforcement learning, graphical models, natural language processing, data representation, and computer perception.
Qualifications
The basic requirements for this role are a master’s or doctoral degree in computer science or equivalent field experience. Recruiters usually prefer candidates with skills such as algorithm building, distributed computing and benchmarking, and parallel computing. A concrete knowledge of software architecture is also recommended.
Business intelligence developer
The position of a business intelligence developer is in noteworthy demand and is an excellent AI career choice. The role involves analyzing complex data to anticipate market and business trends with an aim to increase the efficiency and profitability of the organization.
The candidate should have strong analytical and technical skills as well as problem-solving skills. Business intelligence developers are responsible for modeling, designing, building, and maintaining large amounts of data for extensive and complex cloud data platforms.
Qualifications
Candidates should possess a bachelor’s degree in engineering, computer science or a related area. On-the-job experience and a combination of certifications are also preferred. The ideal candidate will have experience in data mining, data warehouse design, SQL queries, and certifications in data science.
Get going!
The economy is doing well. Tech companies have been doing well. If you want a sunny AI career, there are multiple ways of making this happen. Getting the skills listed above — and hard work — are key aspects no matter which direction you choose.
Featured image: Pixabay
