When OpenAI launched ChatGPT in November 2022, mass adoption of artificial intelligence (AI) came sharply into focus, with the chatbot crossing 100 million users just two months later to become the fastest-growing consumer application.
In fact, according to a state of AI report from McKinsey, AI adoption has more than doubled globally from 2017 to 2022.
Race to the top
Today the race to not only match ChatGPT’s capabilities, but eclipse them, has meant some of the biggest players in tech have been busy creating their own versions.
Microsoft has invested $10bn (and counting) to bring OpenAI’s tools to its Bing search product. Meanwhile, Google has just announced it is merging its two AI-focused divisions, Google Brain and DeepMind, to keep up with industry developments.
“The pace of progress is now faster than ever before. To ensure the bold and responsible development of general Al, we’re creating a unit that will help us build more capable systems more safely and responsibly,” CEO of Alphabet, Sundar Pichai, announced in a blog post on the company’s website.
This comes after Alphabet’s chatbot Bard lost the company $100m after inaccurate information was shared in an advertisement following its launch.
Closer to home, Chancellor Jeremy Hunt has voiced his desire to spur the UK’s commitment to AI investment and integration.
This includes establishing the UK as a technological hub for AI innovation and research and funnelling £2.5bn into a quantum computing strategy by 2033.
Looking to the future
With so much accelerated investment and a realignment of priorities taking place, the good news for tech workers is that a career in AI is not only at the forefront of cutting-edge innovation and development, it looks set to enjoy stability and a high salary now and into the future.
And while the headlines surrounding mass tech layoffs can’t be ignored, or the experiences of those on the receiving end of redundancy diminished, when it comes to AI and machine learning (ML) capabilities, developers and engineers are still in high demand.
There has been a 14% increase year-on-year in the number of automated jobs, and figures from the World Economic Forum indicate that the rapid growth of AI will create another 95 million high-paying jobs by 2025.
Taking all of the above into account, there’s never been a better time to pivot to a career in AI. Or, if you’re already working in the field, move to an organisation that is prioritising machine learning skills. Below are three companies that are currently hiring but you can also find thousands more opportunities via the UKTN Job Board.
Product owner for AI Product, microTech Global, London
microTech is working with a leading journal for scientific publications to hire a product owner to create and manage data products, translate product manager strategies to tasks for development, serve as a liaison between teams, and streamline the execution of product priorities.
To apply you should have prior experience as a product owner in a similar position, experience with cloud data platforms and data pipelines, experience using languages like SQL, R and Python and strong analytical skills.
See the full job description here.
Senior DevOps engineer, Third Republic, London
Third Republic is hiring for an exciting startup company transforming a niche area of transportation. As a senior DevOps engineer, you will deliver and improve the support engineering process, install and implement a mix of on-premise and cloud infrastructure and build scalable, production-ready solutions.
Applicants should have a deep understanding of networking fundamentals, knowledge of Linux, familiarity with AWS services and networking and experience deploying containerised applications and workloads.
DevOps consultant, IBM Consulting (UKI), IBM, London
As a DevOps consultant at IBM, you will work in a fast-paced and dynamic environment to support leading clients in delivering meaningful change to their organisations. This will include implementing custom solutions, as well as using open source DevOps tools.
Required technical skills include extensive experience with CI/CD tools and different automation technologies, experience using infrastructure as code and configuration as code tools, containerisation experience working with Kubernetes and Docker, and writing scripts to achieve automation and serverless architecture interfacing with relational databases and No-SQL databases.
This article is part of a paid partnership with careers marketplace Jobbio to share the most exciting UK tech jobs with UKTN readers.