Since the day a hiring manager first wheeled a whiteboard into a conference room, software engineers have dreaded the technical interview, which can be an all-day process (or multi-day homework assignment). If you’re interviewing for multiple roles, you can expect to write out a bubble sort in pseudocode for each one. These technical interviews do no favors for hiring companies, either, because the investment needed from both parties limits the number of candidates a company can consider. In this age of data-driven decisions, perhaps there’s a way that AI and ML can help candidates and companies find each other.  

On this episode of the podcast, sponsored by Turing AI, we chat with Chief Revenue Officer Prakash Gupta about building a better hiring process with AI. Turing helps companies scale their engineering programs quickly with remote developers from around the world. We talk about how to vet a profession without standard markers, the benefits of soft skills, and how AI-assisted hiring helps everyone involved. 

While companies have been outsourcing development for years, COVID made the software industry almost entirely remote. Suddenly, every company has the ability to hire the best developers regardless of location. And good developers can find work at companies of all sizes without packing up and settling in Silicon Valley. 

But when any company could conceivably interview any candidate, how do you vet candidates at scale? There is no standardized board certification for software engineers, after all. Every interviewer has to vet the candidates themselves, and that’s where human biases come in. 

On one side, you have Fortune 500 companies developing complex systems and undergoing digital transformation projects, plus startups looking to scale their engineering organizations as their product finds market fit. On the other, you have a new generation of engineers trained on bootcamps and online resources who may not have opportunities where they live. That’s where Turing comes in, matching 1.7 million engineers from over 140 countries with jobs at hundreds of companies. 

Turing strives to mitigate bias by collecting hundreds of signals about candidates over a four- to six-hour process. This process covers projects candidates have worked on, technology aptitude, and soft skills through 30-minute tests, candidates’ online presence in places like GitHub and Stack Overflow, and qualitative assessments refined over two years of feedback loops. 

A process that once consisted of ten interviews can now drop to two or three at the most. Some Turing customers have eliminated interviews altogether, relying on Turing’s AI-powered solutions to surface and evaluate the best candidates. To see how Turing can streamline your interview process, either as a candidate or a company, check out turing.com today.

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