Free catered lunch and a dog-friendly office are two of the perks offered by an educational technology company in Palo Alto, Calif., that’s looking to hire a machine learning engineer. The position, posted on Dice, will pay between $140,000 and $160,000 to the right candidate who’s skilled in machine learning platforms as well as data mining, statistical modeling, and natural language processing.
Job-seekers who possess those skills typically could expect multiple job offers, says Matt Leighton, director of recruitment at Mondo, which specializes in digital marketing and technology staffing. The job titles vary from company to company; some might post positions in search of a data scientist or machine learning engineer, others might be after a natural language processing (NLP) programmer or cognitive computing engineer.
But hiring companies are seeking the same talent: "They're people who create algorithms through code that allow computers to self-learn,” Leighton says. "That's the future. That's artificial intelligence, that's [IBM] Watson, that's everything that is predictive analysis, forecasting, analytics. That's what we get requests for all the time."
Companies are paying top dollar for people with these skills. "A good data scientist who can do predictive analytics using the language R to help computers self-learn, so to speak – those people can get $120 or $130 an hour, or $200,000 a year,” he says. But they’re hard to find and typically wind up with multiple suitors. "There’s not enough supply out there to meet the demand. Any candidate that has this skill set will be interviewing for five or six or seven different positions.”
"Unity engineers are going for over $100,000 now. When I first started seeing the requests come in, they were more like $70,000 or $75,000,” Leighton says. “Developers are smart; they know they have something niche, and they know they can start charging more."
Demand for machine learning experts and virtual reality pros is spiking as enterprise adoption of these technologies grows.
While the concepts of machine learning aren’t new, adoption among businesses is becoming more pervasive. Consumers are accustomed to shopping recommendation engines that anticipate probable purchases, and they’re growing more dependent on driving optimization tools that use sensor data to suggest less congested traffic routes.
Companies that are making the transition to digital businesses aim to make better use of all the data they’ve been gathering and analyzing – creating new business opportunities and new ways to reach customers. Research firm IDC forecasts global spending on cognitive systems will reach nearly $31.3 billion in 2019 with a five year compound annual growth rate of 55%.
What does that mean for technical talent? Roughly 36% of all developers who are actively working on big data or advanced analytics projects now use elements of machine learning, according to a new survey from Evans Data.
Likewise, virtual reality is making its way out of niche applications and into the broader corporate landscape. Lower cost and higher quality motion sensors, screens and processors are fueling enterprise interest in virtual reality technology for applications such as prototyping, product development and virtual showrooms. Research firm Forrester estimates that 52 million units of VR head-mounted displays will be in enterprise and consumer use in the U.S. by 2020.
"I think [virtual reality] is as forefront in American society as it's ever been,” Leighton says.
A third area that’s driving new demand for skilled talent is the distributed ledger technology blockchain.
"The use of blockchains, of which bitcoin is but one implementation, has the potential to deliver disruptive change, as cryptocurrency-based technologies become more widely adopted and evolve to powerful decentralized platforms supporting diverse scenarios for value exchange," writes research firm Gartner, which predicts that by 2020, autonomous software agents outside of human control will participate in 5% of all economic transactions.
"Getting money quickly from platform to platform – that is an ecommerce company's golden ticket," Leighton says. But it’s still a niche skillset. According to Mondo, a blockchain engineer’s job responsibilities could include building, maintaining, and upgrading infrastructure that supports blockchain nodes; working within the company to develop best practices in order to improve the setup; and staying on top of the latest programming languages. Along with analytical skills and knowledge of different programming codes, blockchain engineers need an understanding of blockchain protocols including bitcoin as well as the ability to work within mobile, e-commerce, and cloud-based platforms.
Use in financial services isn’t the only avenue for blockchain applications. Companies in healthcare and supply chain, for example, are also finding emerging use cases. "We see a lot of people that are trying to get into it,” Leighton says. "It's something that a lot of people talk about, but it's not something that a lot of people do." (See: Blockchain: You’ve got questions; we’ve got answers)
In the bigger picture, overall IT hiring remains robust. In the second half of 2016, 21% of CIOs surveyed plan to expand their technology teams, according to Robert Half Technology. Sixty-three percent of CIOs intend to only fill open roles, 13% anticipate putting hiring plans on hold, and 3% expect to reduce their IT staff in the second half of the year.
"The real technical people? They don't stay on the market for more than two days. They're always off the market," Leighton says of the hiring climate for IT pros. As companies struggle to find the talent they need, they’re bolstering their employment packages to include more benefits and perks. Telecommuting, in particular, is becoming a must-have option, Leighton notes.
"If you're looking for a high-end developer or subject matter expert on a particular technology, it's almost goes without being said that they'll be able to work from home.”
Join the CIO Australia group on LinkedIn. The group is open to CIOs, IT Directors, COOs, CTOs and senior IT managers.