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Emerging AI Careers
AI is changing many current tech jobs. It’s also creating new job titles and opportunities that are going to emerge in the next few years.
How is AI creating new opportunities in existing tech jobs?
What are some emerging careers?
AI is creating new opportunities in tech careers
There are several careers that are increasingly in demand as AI grows. Here are 4 sure bet high growth jobs that are at the center of work in AI.
Machine Learning Engineer
The Machine Learning Engineer’s job is to:
Gather data about how users play the game. This data will be used to ‘train’ the AI program.
Analyze the data to look for ways to make the game more challenging
Build new challenges and test them with a sample set of data. In other words design the "brains" (algorithms) that allow the program to learn from the data
Train, Test and Optimize. Test to see how well the machine has ‘learned’ and make improvements if necessary.
Work with Product and Project Managers to put the game in real-world situations.
Machine Learning Engineers are deep in the world of AI and data.
At the center of AI is machines learning to do tasks, so “teaching” machines to learn is a key function in all AI careers. This is the area that Machine Learning Engineers specialize in. Machine learning engineers create programs for machines to learn.
Suppose you are working on the design of a game - it could be educational or fun or both. You want the game to be challenging so that the more you do, the harder it gets and users won’t get bored. How can machines ‘learn’ to do this?
Data Analyst
Data Analysts provide insights that solve real-world problems.
Suppose you are a Data Analyst who works for an online retail site that sells jewelry or clothing. You may be asked to help the company understand the shopping behavior of teenage customers. By analyzing sales data, customer feedback, and market trends, data analysts can provide recommendations on product assortments, pricing strategies, and promotional offers.
You use data all the time. For example, if you’re comparing the win / loss record of your favorite sports team, or deciding which subway is the fastest to get somewhere. That’s where the work of a Data Analyst starts.
The job of the Data Analyst is:
Data Collection and Interpretation: For example, collect data about what teenagers purchased over the last year, compare purchases of jewelry items, T-Shirts and sweater
Extract key information from data sources to solve problems, and feed into AI tools. For example, identify patterns and trends in sales of particular items of clothing
Analyzing Trends: Work alongside the business team to use the data to answer questions like - which particular items are most popular among buyers who are 16-18 years old, at what time of year do teens buy more jewelry?
Decision Support: Uses statistical techniques to provide actionable insights - for example, which product will likely sell the most during the holiday season? Which jewelry designer’s products are most popular?
Reporting: Creating clear visualizations like graphs to depict complex data in a simple and understandable way, leveraging AI tools to be able to work faster
For more information about a career path as a Data Analyst, Click here
ETL Developer
The main tasks of the ETL Developer will be to:
Extract the Data: Pull data from various sources - like patient records, pharmaceutical data, medical studies about patients with similar ailments, etc.
Transform the Data: ‘Clean’ and validate the data to ensure that it is accurate and reliable - for example it shouldn’t include data about medicines and drugs that have known harmful side-effects, make sure that patient privacy is not compromised. This gets it ready to be used by the AI program and will be accurate.
Load the Data: Upload the refined data into databases or data warehouses that can be accessed by other teams to analyze and make healthcare decisions that trained medical staff can use when treating a patient. The database is where the AI program will ‘pull’ the data it needs from.
For more information about a career path as an ETL Developer, Click here
If you’re interested in the work of a Data Analyst or Machine Learning Engineer, another path in your career could be an ETL Developer. ETL Developers dive deep into understanding where data comes from and finding new ways of using it. Extract, Transform and Load (ETL) Developers are the magicians who transform raw data into meaningful information, ready for analysis and action by either AI programs or Data Analysts. AI is like an engine that constantly needs to be fed usable data. ETL developers are like the fuel that keeps the AI moving.
An ETL Developer works on simplifying the data by automating the extraction, transformation, and loading (ETL) of the data. For example, suppose you are working on a healthcare analytics platform and you want to enable an AI program that will quickly get and highlight information that affects the health of patients. The faster and more accurately you can get the information to the AI program being used by the healthcare providers, the quicker people can get the care they need.
AI Software Developer
You may have heard people say that Software Developers will no longer be a necessary job when AI and machines learn to write code. While we can’t predict the future, we can say with certainty that AI Software Developers are at the heart of creating the software that houses AI applications. They bridge the gap between complex machine learning algorithms and user-friendly software.
An AI Software Developer might work on creating a smart virtual assistant for a voice activated speaker like an Amazon Echo. They collaborate with a Product Manager to identify what the program should do. Then they work on programming the software that uses AI to interact seamlessly with their smart speaker.
The main tasks of and AI Software Developer are to:
Design a software framework and then code the software. AI Software Developers will collaborate with the Data teams to identify the best way to use the data to achieve a goal.
Implement AI algorithms and models into the software
Test and debug to ensure the software operates smoothly and reliably - often using AI testing tools.
Ensure software meets all requirements of quality, security, modifiability, extensibility etc. and continuously upgrade the software to incorporate new AI advancements
For more information about how to get started in a career path as a AI Software Developer, Click here
Predicting AI Job Growth
AI is such a rapidly developing field that new careers are opening up all the time. Here are some jobs that are emerging now. It’s not clear these will all be around for the long-term…
Have you ever wondered how ‘smart’ cars can navigate around the streets? How are the cars' cameras able to identify different objects so it can navigate on its own?
That’s what a Computer Vision Scientist does. They come up with ideas and programs that better help computers to ‘see’. They develop algorithms that get trained on pictures and videos so that the program can identify objects that they are shown. It’s one of the most exciting and cutting-edge parts of the AI and data world.
When you ask tools like Chat GPT or Bard to do things for you, how do they almost always seem to understand what you’re asking?
That’s what a Prompt Engineer does. Prompt Engineers curate and design the prompts that guide chatbots in interpreting and responding to human input. They ensure the flow of conversation feels natural and the bot’s responses are accurate and helpful. The Prompt Engineer is the human who translates language so machines can understand it, and generates the best possible response.
If you don’t plan on a career focused on the data side of AI, but you’re still interested in the sector consider AI Sales careers.
Bridging the gap between complex AI technologies and client needs is the task of AI Sales. They understand AI’s potential and help clients identify how AI solutions can benefit their operations.
The success stories of AI in reducing operational costs and boosting efficiency is driven by insightful AI Sales Executives.
A background in sales or marketing along with a keen interest in understanding and explaining technology would prepare you for this role.
Another less technical AI career opportunity is AI Product Management. They will take an idea all the way from a sketch on a napkin to a market-ready solution.
AI Product Managers are the glue between technical and business teams so that AI products like Siri or Alexa are designed for what people are looking for and make money for the company. People who have a good mix of technical knowledge, management skills, project management, and marketing will do well in this role.
Behind every groundbreaking AI innovation, there's a team of diligent AI Research Assistants. They support the research agenda, performing experiments, and analyzing data to push the boundaries of what AI can achieve.
It’s a great way to get started in AI and data, and companies and colleges are constantly seeking sharp minds to support their AI research endeavors.
Another good way to get started in AI could be training and testing.
Every AI system needs to be taught and tested, a role perfectly suited for AI Trainers and Testers. They ensure that AI systems respond accurately and reliably before they are deployed.
Companies like OpenAI often require a team of trainers and testers to fine-tune their AI models.
As AI programs get bigger and more complex, it’s essential to have someone making sure they function and integrate the way they should.
The seamless running of AI systems within an organization is the responsibility of AI Operations Associates or Managers. They ensure that AI systems are well-integrated, maintained, and improved over time. Companies like Microsoft have dedicated AI operations teams ensuring that their AI-driven services are high quality.
