The Roles of AI Professionals: A Quick Guide to the Field
Artificial Intelligence (AI) is a hot topic, and its tools are becoming part of our daily lives, both at home and at work. When it comes to the technical professionals behind these tools, the field is more complex than you might think. AI is an umbrella term that includes a variety of constantly evolving technologies.
When you need an AI expert for your team, what skills are you actually looking for?
To help you quickly understand this complex field, here’s a practical guide from a tech recruiter’s perspective on the skills behind the professional titles.
Professionals Working with Numerical Data
These roles focus on analyzing and classifying structured, quantitative data. Here are two examples of common roles working with raw numbers:
Data Scientists analyze complicated datasets and statistics and based on these, help organizations make informed, data-driven decisions. They build analytics to solve different business problems.
Machine Learning Engineers design, create, and deploy the machine learning models and algorithms. Their work can be anything from predicting stock market trends to making sense of sensor data from IoT devices like smartwatches or industrial machinery.
Professionals Working with Unstructured Data
These roles specialize in creating, interpreting, and understanding non-numerical data like text, images, and video. Generative AI is often related to this kind of data since, in addition to its ability to understand the data, it uses that understanding to create new, realistic content.
Examples of roles in this field are:
Natural Language Processing (NLP) Engineers teach computers to understand and produce human language. This work is essential for the functionality of chatbots and language translation applications, for example.
Computer Vision Engineers give “eyes” to computers. They build systems that are able to understand visual information from images and videos. For instance, self-driving cars, robotics, and facial recognition systems benefit from technology like this.
While this division is one way to simplify a complex field of AI roles, it’s important to remember that many roles require a mix of skills to handle different data. The truth is that job titles in AI are not that consistent yet and the field is evolving fast.
Where does the Mythical AI Developer fit in?
AI Developer is a software development professional specialized in applications with AI functionality. Like Fullstack Developers, they are experts in integrating pre-built models (e.g. GenAI language model) into software applications like mobile apps, websites, and business systems. They write code to manage data pipelines, handle API calls, and ensure the entire system is effective, secure and accessible to the end user.
The AI Professionals Beyond the Code
In addition to hands-on technical professionals there are roles like AI Strategists and AI Architects, who have a wider, strategic and often closely business related perspective on AI. These senior professionals help to decide which AI tools would best benefit the organization. The architecture and design of the overall AI system are typically their responsibility. Organizations need their expertise when evaluating the effectiveness, scalability, and cost-efficiency of different AI options available.
Navigating the world of AI talent can be complex, but Talented is here to help.
Contact us and we’ll help you find the AI professional you are looking for!
This blog post is a simplification written for non-technical professionals. The text was written by Kreetta Luoma inspired by a discussion with Mikko Kontsas (Business Unit Director, AI & Data, Witted). Gemini was used to check the grammar and fluency of the text.