In-Demand Skills for Generative AI Jobs

From data processing to ethical AI & bias mitigation, here are some of the most sought after skillsets for GenAI jobs: 

Natural Language Processing (NLP)

According to IBM, NLP combines computational linguistics with “statistical and machine learning models to enable computers and digital devices to recognise, understand and generate text and speech.” Given the increasing popularity of text-based GenAI applications such as ChatGPT, proficiency in NLP is invaluable. 

Skills in pre-processing techniques, sentiment analysis and language generation algorithms are sure to make you an in-demand asset for organisations working with conversational agents and text generators. Experts such as Research Engineers, Software Engineers and GenAI Engineers all require proficiency in NLP. 

Data Processing & Visualisation

GenAI heavily relies on datasets, so the ability to pre-process, clean and manipulate data efficiently is key for any GenAI expert. Proficiency in data visualisation through libraries such as Bokeh, Ggplot2, Matplotlib and Plotly is also essential for comprehending the intricacies, patterns and characteristics of your datasets. 

Model Tuning

Model tuning refers to the process of identifying, establishing and optimising various parameters and hyper parameters of AI models to achieve desired outcomes. These include improving accuracy, reducing errors or enhancing the quality of generated content. Model tuning requires a solid understanding of the underlying algorithms and techniques used in generative models, plus proficiency in machine learning. Jobs in this area include Machine Learning Engineers, Data Engineers, AI/Machine Learning Scientists, AI Consultants and Data Analysts. 

Ethical AI & Bias Mitigation

With concerns around AI ethics and bias growing, individuals with skills in ethical AI practices and bias mitigation techniques are increasingly sought after. In fact, Salesforce survey respondents were almost unanimous (99%) in saying their business must take measures to ensure GenAI is used responsibly. Specialised AI jobs in this field include AI Ethics and Governance Analysts, AI Ethics Consultants and AI Ethicists. 

Top Developer Tech for GenAI 

Careers in artificial intelligence often require specialised knowledge of specific programming languages, libraries, chatbots and models. If you’re wondering how your current skillset fits into the GenAI landscape (and if you need to learn any new tools!), we’ve put together a list of the most commonly used technologies in the sector. 

• Python: With an extensive array of libraries and frameworks such as PyTorch, TensorFlow, Keras and GPT-3, Python provides the backbone for many GenAI models. Proficiency in Python is essential for pursuing a GenAI career – including Machine Learning Engineers, Software Engineers, Data Analysts and AI Consultants. 
• TensorFlow: Google’s, open-source deep learning software library is commonly used in GenAI projects. It’s used in advanced generative models for a wide range of applications, with a particular focus on the training of deep neural networks. 
• PyTorch: Another popular machine learning library developed by Meta AI. PyTorch is known for its flexibility, experimentation and quick editing capabilities for models. 
• ChatGPT: Now almost a household name, OpenAI’s natural language processing model is well-known for its conversational abilities. Mastery of ChatGPT is useful for professionals involved in text-based GenAI applications, enabling them to create engaging and human-like interactions in chatbots, virtual assistants and dialogue systems. 

Transferable Skills for AI Job Opportunities

GenAI jobs are not limited to individuals with highly specialised experience in artificial intelligence or a PhD in computer science. Much of this field also requires people with mainstream tech skills, including: 

• Data science & analytics: Data processing, model tuning and data visualisation are three key skills for GenAI roles – meaning data science & analytics professionals’ skillsets complement these roles seamlessly! Analysts’ strong foundation in statistics, data manipulation and exploratory data analysis can give them a segue into roles such as Machine Learning Engineer & AI Data Engineer.
• Software engineering: Software engineers’ expertise in the software development lifecycle, version control and debugging is essential for building scalable and maintainable GenAI systems. Programming languages such as Python and Java are also essential for developing and deploying generative models.
• Domain knowledge: Expertise in specific industries such as healthcare, finance, or marketing makes candidates suitable for upskilling into careers in artificial intelligence within their domains. Having deep industry knowledge gives you the ability to collaborate with GenAI professionals to create solutions – an increasingly important skill in future development environments.

Get Connected with a Technology Recruitment Agency 

Whether you’re a seasoned professional on the hunt for your next AI role or looking to transition from another domain, our expert team here at Emanate Technology has you covered. As a specialist Australian technology recruitment agency, we’re dedicated to connecting talented individuals with rewarding tech jobs. Contact us today to take the next step in your GenAI career journey!