In the past three years, Machine Learning has been one of the toughest jobs to fill for any organization. With top firms like Amazon and LinkedIn spending millions annually on recruitment, how can smaller firms stake their claim when it comes to niche ML talent?  To give an example of how difficult it is to attract machine learning resources, a study by Paysa shows that Amazon’s average annual investment in AI and machine learning recruitment is $227.8 million, with the second major competitor being Google with an annual investment of $130.1 million.

If you are a hiring manager or sourcing specialist who doesn’t have access to similar funds or recruiting team, then you’ll have to think out-of-the-box to stay competitive. The following four candidate sourcing channels will help you recruit qualified ML talent.

1) Partner with Universities

Funding a school project or partnering with a university for paid internships can open a new source of machine learning talent for your firm. Given the short supply of AI talent, this has become an incredibly effective way to recruit ML talent. Companies can also organize hackathons and specialized training programs to find new talent who is acquainted with the latest tech and skill-sets.

These are some of the top universities that offer Masters in machine learning.

  • University of Michigan Ann Arbor
  • Berkeley
  • Cornell
  • Columbia University
  • University of Washington
  • University of Massachusetts Amherst
  • John Hopkins University
  • Penn State University
  • California Institute of Technology

2) Collaborate with a Tech Staffing Agency

With limited talent pool of high-end and experienced candidates, some companies prefer to reach out to external recruitment agencies to fill their available ML and AI roles. Businesses with limited recruitment resources feel that outsourcing their needs is the most cost-effective and efficient option to overcome the challenge of procuring ML roles. The exclusive network of passive and pre-vetted AI talent that tech staffing agencies have helps firms in reducing their time-to-hire and cost-to-hire metrics.

3) Create an Account on Referral Platforms

You can also create an account on referral platforms that have a solid user base of technology professionals. These platforms run referral campaigns on different mediums (email, social media campaigns etc.) based on your experience and location requirements. Referral platforms are a great way to find niche talent that is not available on job boards and social media.

Some of the top referral platforms are:

  • Role Point
  • Refer a Gig
  • Simppler
  • Zalp
  • Perks

You can also use Direct Sourcing platforms like TalentDome which maintain a pre-vetted talent pool for different industry professionals. Using sophisticated candidate-matching algorithms, TalentDome helps firms get large-scale referrals from silver & bronze candidates.

4) Professional Meet-ups & Social Media

Social media can be a crucially useful tool in ML recruiting because of the demanding nature of these jobs. Research also suggests that Linkedin may be a better choice for specific job types than others. Another great source for machine learning talent is the local meet-up groups in the USA. Some of the top meet-up groups with which you can share your job openings include:

  • Data Driven NYC (New York, USA)
  • NYC Machine Learning (New York, USA)
  • Advanced KubeFlow Meetup (San Francisco, USA)
  • Bay Area Spark Meetup (San Francisco, USA)

Apart from utilizing these sourcing channels, make sure you invest in your employer brand by promoting career progression stories, employee benefits, and flexible leave policies. To attract top talent, it’s important that you maintain an employee-friendly image on your website, social media accounts, and career fairs.

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