How Lyft Drove Early Career Engineering Quality at Scale

Lyft’s commitment to delivering world-class transportation experiences starts with investing in hiring top engineering talent. Innovation and product growth depend on the engineers who build them. To effectively hire and build strong engineering teams, Lyft’s University Programs Team needed a faster, more reliable way to evaluate candidates from universities around the world.

What Challenges Did Lyft Face in Early-Career Hiring?

As university recruiting ramped up, Lyft’s teams faced increasing pressure to hire quickly without sacrificing quality. But early-career hiring brings unique challenges:

• High candidate volume makes it difficult to identify top engineering talent across global applicant pools.
• Limited real-world experience makes it challenging to reliably gauge a candidate’s job readiness and ability.
• Internal bandwidth constraints slows interview timelines and diverts engineers from building core product features.
• Pedigree-based screening risks overlooking high-potential candidates from nontraditional backgrounds.

Collectively, these obstacles create friction at the top of the funnel, slowing hiring, straining internal teams, and putting quality at risk.

How Did Karat Help Lyft Evaluate Real-World Engineering Skills?

Lyft redesigned its early-career engineering hiring process using Byteboard’s project-based interviews to evaluate real-world engineering skills. The new interviews improved the signal on technical ability, enabling Lyft to focus on a candidate’s ability and bring consistency, speed, and equal opportunity to its early-career hiring process.

With Byteboard in place, Lyft now:

• Surfaces top candidates from large applicant pools through a consistent, high-signal evaluation focused on problem-solving and engineering fundamentals.
• Generates a stronger signal on practical, real-world skills with scenario-based evaluations aligned to Lyft’s day-to-day engineering work.
• Reduces engineering involvement by shifting early-round evaluation away from internal teams, allowing them to focus on team fit in later-stage interviews.
• Leverages a resume-agnostic process that gives every candidate, regardless of school or background, an equal opportunity to demonstrate ability.

Together, these changes enabled Lyft to evaluate talent efficiently and effectively without compromising on quality.

What Results Did Lyft Achieve with Karat?

By reinvesting in its technical evaluation process, Lyft built a stronger foundation for early-career hiring. More candidates could be evaluated, engineers were hired faster, and the overall level of engineering talent was elevated.

• Increased volume – Candidate volume up 5x without overwhelming internal teams
• Faster hires – 78% of roles filled in under two months (up from 50%)
• Accelerated the interview process – Time to complete technical interview cut in half

This shift empowered Lyft to operate at scale while staying true to its high talent bar and commitment to inclusive growth.

Ready to accelerate your early-career hiring? Request a Demo.

How Did Lyft Build a Long-Term Advantage in Hiring Top Engineers?

What began as a tactical change became a strategic advantage. Lyft now runs a high-throughput early-career hiring engine that reflects its high engineering standards and company values. The result: a stronger, more diverse pipeline of engineers, equipped to drive Lyft’s next era of growth and innovation.

See how Karat’s Byteboard can help you scale early-career engineering hiring. Request a Demo.