AI talent characteristics – global
Amazon, Google, Facebook and Microsoft are the top companies recruiting for AI/ML/Big Data talent. These companies, in their bid to incorporate AI tech in their products and to power their internal applications and processes, will have strong demand for such talent in the immediate term. The Big Tech companies have a large bench of AI talent along with late-stage/mature start-ups. The availability is limited and the competition to attract and retain talent is fierce. Estimated demand for AI/Big Data talent was ~1.2 million, whereas 650K was the total installed talent globally. The rest (~50%/515K) of the positions were vacant (based on an estimate of available job openings across job boards, LinkedIn).
Apple, Amazon, Google, Tesla, IBM and Accenture are investing heavily to acquire talent (talent acquisition cost) and create capacities internally and externally to develop talent pools to hire from. This involves setting up research labs, innovation centers, hiring Ph.Ds from Universities, massive up-skilling program.
While the US AI/Big Data talent pool stood at ~280K, there were 310K unfilled jobs in 2018. Global corporations employ ~110K AI resources, while start-ups have an installed talent base of ~160K. Machine Learning, Deep Learning, Reinforcement Learning, Neural Networks, and Computer Vision are the top skills in demand within the AI/Big Data talent space. Strong software development skills are also in demand – C++, Java, Linux, Python etc. US companies have invested US$1.35bn in hiring AI talent between April & September 2017; Microsoft has entered 2019 leading the AI patent race with 697 qualifications and is one of the top AI talent recruiters in the US today. Companies like Microsoft, Apple, Facebook are paying top dollars to onboard not only University graduates & Ph.Ds but also deep learning academics & scientists to man positions in research in AI labs and Centres of Excellence. In the Bay Area both big technology companies and well-funded start-ups vie for AI talent; median salaries have topped US$195K-200K; Data Science is one of common roles with emphasis on building cross-industry AI platforms.
Approximately 1,500 AI start-ups operate from Bay Area and are one of the lucrative destinations for AI talent. Operating in 4 key technology areas within AI – Core AI, Computer Vision, NLP and Data Science. Platform start-ups with strong VC backing are hiring laterally from tech giants like Adobe, Google, and Microsoft. Google and Facebook have hired experienced engineers from peer tech companies many of whom are graduates of Tier 1 US universities; Apple and Uber have hired from Microsoft as well as from Google
Seattle has the second largest concentration of AI talent after the Bay Area; majority of the talent are in Data Management & Data Scientist roles in large global corporations including tech companies as well as in industry/vertical-specific start-ups
The average annual salary of an AI Engineer works out to be US$241,145, according to Paysa.com. The share of AI jobs is rising steadily owing to large-scale adoption & assimilation of new technologies within product lines; Microsoft is looking to hire ~2,000 AI resources globally, AI jobs constitute a 3rd of NVIDIA’s total job adverts