The last technical interview you'll ever take

The last technical interview you'll ever take

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.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(996)

Elevators, toasters, and the birth of Java

Elevators, toasters, and the birth of Java

Ryan sits down with James Gosling, creator of Java at Sun Microsystems, to talk about the early networking friction that drove the need for interconnectedness, the stringent reliability requirements o...

27 Okt 36min

Rumors of the SaaS demise are greatly exaggerated

Rumors of the SaaS demise are greatly exaggerated

Recorded on the floor of LDX3, Ryan chats with Nivia Henry, an engineering leader most recently at Netflix, about the reality of the supposed SaaS apocalypse, the complex calculus of the modern build-...

23 Okt 25min

Don't forget about the UI for AI

Don't forget about the UI for AI

Recorded at OpenAI Dev Day 2026, Ryan sits down with Andrew Ambrosino, member of the technical staff at OpenAI, for a conversation on OpenAI's strategy for merging ChatGPT and Codex into a unified exp...

20 Okt 24min

AI says you’re right, formal methods say you’re wrong

AI says you’re right, formal methods say you’re wrong

Ryan is joined by Gabriela Moreira, CEO at Quint, about why formal specification languages like TLA+ are essential for catching system design flaws before writing code, how Quint brings developer-frie...

16 Okt 28min

Keep calm and call clone with Rust

Keep calm and call clone with Rust

Ryan sits down with Josh Triplett, member of the Rust Leadership Team at the Rust Project, to chat about how the borrow checker delivers compile-time memory safety without garbage collection overhead,...

13 Okt 43min

Taking a look under your agent’s hood

Taking a look under your agent’s hood

Ryan is joined by Yanbing Li, Chief Product Officer at Datadog, to talk about applying observability to non-deterministic AI agents, blurring the boundaries between software development and production...

9 Okt 33min

Tales from the 2026 Developer Survey results

Tales from the 2026 Developer Survey results

Ryan chats with Erin Yepis, Senior Analyst at Stack Overflow, about the results from this year’s Annual Developer Survey, including the overwhelming daily usage of AI coding assistants despite lingeri...

6 Okt 32min

Constraints that make developers faster

Constraints that make developers faster

Ryan chats with Julien Verlaguet, CEO at Skip Labs, about finding the balance between human tolerance and tooling constraints, the spectrum of typed programming languages, and building cost-effective ...

2 Okt 28min

Populärt inom Business & ekonomi

framgangspodden
bathina-en-podcast
rss-jossan-nina
varvet
rss-borsens-finest
rss-hos-psykologen
rss-svart-marknad
badfluence
avanzapodden
uppgang-och-fall
rss-inga-dumma-fragor-om-pengar
24fragor
rss-dr-bjorklund
lastbilspodden
fill-or-kill
rss-dagen-med-di
tabberaset
rss-kort-lang-analyspodden-fran-di
borsmorgon
dynastin