If your company is in the technologies industry (or dabbling therein), it's a safe bet you're in the market for a machine learning engineer. These engineers are responsible for programming machines to learn from experiences and behave accordingly, and in doing so, they run everything from conducting experiments to deploying and optimizing solutions. It all sounds a bit futuristic, right? Well it is and it isn't.
The notion and field of machine learning has actually been around for decades — remember Alan Turing? — but has enjoyed a recent rise thanks to the resurgence of artificial neural networks in practical applications. The end result being machine learning engineers are now one of the fastest-growing and most in-demand jobs in engineering. In fact, Burning Glass data shows that there have been more than 12,000 job postings for machine learning engineers in the past year alone — and demand is expected to continue increasing 12x year over year.
So how can your company hire a top-quality machine learning engineer in such a competitive market? To start turning this challenge into an opportunity, we've outlined some steps to take when looking for your next great hire:1. keep your hiring process as efficient as possible 2. find out what constitutes a competitive salary 3. decide which top skills the candidate will need 4. create an eye-catching and engaging job description 5. learn about hiring trends in the technologies industry 6. determine the ideal recruitment channels
Ready to dig in and get started? Keep reading for tips on how to address each of these steps.
1. speed up your hiring process
What does low unemployment plus a projected boom in the machine learning market and already high demand for machine learning engineers equal? A fiercely competitive talent hunt. This means that employers looking for engineers should do all they can to speed up their hiring process.
Of course, we're not encouraging being hasty or rash — but rather, smart and streamlined. Use the diagram below to determine where your process might benefit from an efficiency tune-up.
2. develop a competitive compensation package
It's no secret that perks and benefits play heavily into tech talent's choice of employer. In fact, for some they're more of a deciding factor than salary! So regardless of your salary offering (more on that in a moment), be sure to evaluate your current perks and benefits to ensure they'll meet the standard of today's tech world. For example, onsite health and wellness amenities and flexible work schedules can go a long way, even if you're not able to offer the highest salary among your competitors.
Speaking of salaries, a machine learning engineer is one of the highest earning positions in the technologies industry. But don't let that scare you — they're worth every penny. To kick off your research, make use of Randstad's 2019 Salary Guide, which provides national salary averages for this and other important positions. A competitive salary will also vary greatly by region, too. So be sure to use our salary calculator for the most up-to-date, location-specific salary data for machine learning engineers, as well as other key positions in the technologies industry.
3. identify the top skills for machine learning engineers
Before you tackle the job description, it's important to have a good understanding of what skills and experience are necessary for a machine learning engineer to be successful at your company. Get together with key leaders on your engineering team and the hiring managers do discuss which skills are most needed (your "must-haves"), and which would be a bonus (your "nice-to-haves").
But be careful not to let your bonus skills creep into required skills. While everyone wants to find the most ideal candidate possible — and you should strive for that! — prematurely cutting a candidate loose because they don't possess all your bonus skills could mean missing out on a potential best-fit hire. Machine learning engineers are always hungry to learn, so you can count on just about any candidate being able to pick up any bonus skills you'll need down the line.
Here are the top skills for machine learning engineers, as requested by employers across the nation in the past year:
4. write an eye-catching job description
Your job description should catch candidates' eyes and their interests. Keep the following pointers in mind to ensure your description will appeal to the best applicants out there.
machine learning engineers want to know you understand their value — so highlight the ways your company sees their work as meaningful.
With demand as high as it is, you'll want to learn all you can about how to stand out from your talent competitors. Read up on more insights in our guide to writing highly effective job descriptions.
5. brush up on the latest industry trends
In our fast-paced digital world, future-proofing is a necessity. You're not just hiring for today's needs after all, you want to be proactive in defining what you'll need for tomorrow as well. To be an industry leader, companies must have the right talent — and to get the right talent, companies must have a long-term hiring strategy that's tailored to industry landscape and trends.
Take a look at these trends to know what's currently impacting both the technologies industry and the future of hiring for machine learning engineers:
- Demand for machine learning engineers grew twelvefold between 2014 and 2018.
- This substantial growth isn't expected to slow down at all, given that experts project the machine learning market will reach $8.81 billion by 2022.
- Perks and benefits packages can play a deciding factor for talent. To be competitive, employers will need to make sure their offerings meet (or exceed) what tech talent is coming to expect — especially in California, where demand is nearly four times higher than any other state.
Learn even more about the technologies industry and the shifts and trajectories shaping the hiring landscape in our 2019 trends guide.
California has four times the number of machine learning jobs than any other state.
6. choose your channels to find candidate
Your hiring process is in good order and you've put together a great compensation package. Top skills have been identified, a crack job description is written and you've brushed up on relevant industry trends. Now what? Now it's time to put your posting out there.
Company websites are a good place to start — especially if you've got a robust careers page. Leveraging employee referrals and LinkedIn networks can also yield good results. Job boards are a popular option for finding talent, too. But, if you're serious about finding top talent fast, you'll likely find yourself waiting longer than you'd like for the right applicant to come along.
If you're looking to expand your efforts, consider partnering with a professional staffing firm, which can alleviate many of these worries and risks. When you have industry experts and a prescreened and vetted talent pool at your fingertips, you can feel confident that you're doing all you can to mitigate a bad hire and maximize efficiency.
Want to learn more? Reach out to the experts at Randstad Technologies today to discuss your machine learning engineer needs. Or you can browse our network of quality engineering candidates right now in our Find Employees portal.