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AI Case Study 3

AI Case Study 3

Scaling autonomy engineering across 7 concurrent roles at a $15B AV infrastructure company

Sector: Autonomous vehicles / physical AI

Stage: Late-stage scale-up, approaching IPO

Location: Sunnyvale, on-site 5 days

Roles: 7 concurrent specialist + generalist engineering searches

The brief

The client is the dominant AV toolchain + Vehicle OS + autonomy stack supplier, trusted by 18 of the top 20 global automakers plus DoD programs. At a $15B valuation and planning to hire approximately 250 engineers per quarter, they needed partners who could run multiple concurrent searches without duplicating candidates or drowning their hiring managers in noise.

The 7 roles spanned:

  • Software Architect, Fallback Stack (Trucking)
  • Senior Planning SWE (Trucking)
  • Localization EM (Automotive)
  • Perception SWE (Trucking + Cars)
  • C++ SWE, Onboard / Robotics (Cars)
  • Data / ML SWE (Cars)
  • Backend SWE, Golang (Fallback Stack, Trucking)

The challenge

Defense adjacency complicates visa sponsorship; 5-day on-site Sunnyvale is a hard filter; comp bands range from $280K (generalist Go backend) to $400K+ (Localization EM). Every candidate has to be comp-aligned, relo-willing, and domain-appropriate before we put them into the client’s pipeline.

What we did

  • Built role-specific target maps: Tier 1 AV alumni for specialist roles (Waymo, Cruise post-GM shutdown, Aurora, Motional, Zoox, Argo), passenger-AV crossovers for trucking planning, robotics crossovers for localization and perception
  • Flagged candidates already in the client’s pipeline directly to avoid duplicates
  • Maintained a live rejection list (e.g., candidates who had passed before, relo blockers, comp mismatches) to prevent recycling
  • Ran the searches across multiple recruiters on our team, coordinated through a single account lead so the client only saw one inbound pipeline

Outcome

Ongoing partnership across all 7 roles with weekly pipeline reviews. The model scales with the client’s 250-engineer-per-quarter pace without creating recruiter-on-recruiter conflict.

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