While the above might sound far-fetched, it’s presumably what life could look like if Elon Musk’s Optimus bot gets fully off the ground.
Unveiled at Tesla’s annual AI Day last year, Optimus is a humanoid robot that stands at 5-foot-8 inches, weighs 125 pounds, can walk five miles per hour and lift 150 pounds.
Estimated to cost around $20,000, Musk’s vision for Optimus’ capabilities includes household chores such as tidying up, making dinner, mowing the lawn, shopping for groceries, and taking care of elderly family members. It will also be available to rent by the hour.
The consumer version is predicted to be 10 years away from release, but in the short term, Optimus is scheduled to assist workers in Tesla factories, further fuelling the conversation surrounding AI and automation replacing humans in the workplace.
Direct impact
Aside from amping up automation within manufacturing, how will Musk’s vision impact the tech workforce?
As far back as 2018, McKinsey predicted that AI-compatible roles could increase by 90% in the next decade and it appears this is already coming to pass.
For starters, a bot-filled future is not all bad news for tech workers who have the necessary skills and experience to focus on a role in AI—Tesla itself is currently recruiting for over 50 positions that feature ‘Tesla Bot’ in the job title.
Further proof that tech talent skilled in the intricacies of AI are needed, came courtesy of OpenAI’s on-and-off-and-on-again CEO. Sam Altman’s recent departure and rehiring in November made news globally.
While it’s no surprise Altman was swiftly hired by Microsoft when he was momentarily ousted from the company he co-founded, Microsoft also announced it would hire any OpenAI employees that wanted to follow suit, regardless of the position they previously held.
For now, savvy tech workers who want to future proof their careers can do so in a number of ways including upskilling (OpenAI has devised a series of free courses including a ChatGPT Prompt Engineering for Developers course among others), or pivoting to a role that will allow you to hone your skills and experience while pursuing a career with AI.
If that is the case, the Maddyness Job Board is the perfect place to focus your search as it features thousands of AI roles in companies that are actively recruiting, including the three below.
Data Scientist – Artificial Intelligence, IBM, London
As an AI Data Scientist at IBM, you will help transform clients’ data into tangible business value by analysing information, communicating outcomes and collaborating on product development. You will lead the development and implementation of generative AI models and algorithms for various applications such as computer vision, natural language processing, and audio processing. You will also collaborate with cross-functional teams to identify business opportunities and develop solutions that leverage generative AI technology. View additional details here.
Machine Learning Engineer, Autodesk, London
As a Machine Learning Engineer at Autodesk Research, you will be working side-by-side with world-class researchers and engineers doing fundamental and applied research. The ideal applicant will be a software engineer who is passionate about solving problems and building things as well as a good communicator, comfortable serving as a translator between research and development. As such, you will also collaborate on research projects and papers with a diverse, global team of researchers and engineers and support research through the construction of experimental pipelines, prototypes, and reusable code. See the full job description here.
AI – Machine Learning Engineer, Manager, PwC, Manchester
PwC’s central technology team (Tech Connect) is responsible for identifying and deploying innovative AI use cases for PwC and its clients. The team uses machine learning and natural language processing to build data-driven solutions which solve important problems across healthcare, financial services and professional services. As a Machine Learning Engineer, you will combine and scale natural language models that help subject matter experts (e.g. Risk, Auditing) to efficiently profile and analyse large sets of documents and contribute effective, high quality code. Interested? Apply now.