Aurora
Sr. Staff Technical Recruiter, Physical AI
$162K–$287K
Mountain View, CA +2 · Remote · Senior Staff · Full-time · Posted Oct 29, 2026
- Location
- Mountain View, CA
San Francisco, CA
Pittsburgh, PA - Experience
- 8+ years of technical recruiting experience.
About the job
Leads full-cycle recruiting and talent strategy for Aurora’s senior Physical AI engineering and research searches, partnering with engineering leaders to attract and close highly competitive candidates.
What you'll do
- Own full-cycle recruiting for Staff-to-Principal Physical AI searches across autonomy, ML/robot learning, perception, simulation, controls, AI infrastructure, and hardware engineering.
- Advise VP- and Director-level engineering leaders on market mapping, search design, hiring plans, and candidate engagement and closing strategies.
- Develop Physical AI talent strategy, use data and market insights, improve AI-enabled recruiting, and mentor recruiters and sourcers.
What they ask for
- 8+ years of technical recruiting experience, specializing in autonomous vehicles, robotics, or AI/ML.
- Proven record of closing Staff- and Principal-level engineers and researchers in highly competitive markets.
- Experience advising Director- and VP-level engineering leaders on hiring strategy.
- Ability to use data, market intelligence, and AI tools to shape and accelerate searches; experience with an ATS/CRM such as Ashby and sourcing tools such as LinkedIn Recruiter, Gem, or SeekOut.
Nice to have
- Experience hiring from frontier AI labs or humanoid and general-purpose robotics companies, or building a recruiting function or talent strategy for a new technical domain.
- Experience recruiting research scientists through academic and conference sourcing (e.g., NeurIPS, CVPR, ICLR), or mentoring recruiters and sourcers.
Pay
$179,000 - $287,000 per year (base salary); $162,000 - $259,000 per year (base salary)
Tools
Ashby, LinkedIn Recruiter, Gem, SeekOut, NeurIPS, CVPR, ICLR
AI focus
Recruiting for Physical AI talent across autonomy, machine learning/robot learning, perception, simulation, controls, AI infrastructure, and hardware engineering; use AI tools and improve AI-enabled recruiting practices.
Model-written summary · the original posting is authoritative