Engineering Manager, Computer Vision

This role is hybrid and required in office on Tuesdays and Thursdays.

Hey, we're Glacier! A Series A startup based in San Francisco tackling one of the world's most pressing problems: trash. Did you know that in the US, we send over half of our recyclables to the landfill? We're working to fix that. In doing so, we'll also be reducing carbon emissions, energy consumption, and depletion of natural resources.

Glacier builds custom sorting robots designed to sort apart recyclables as well as AI-powered business analytics that enable recyclers to superpower their plants and improve our society's circularity.

From major CPG companies like Colgate and Amazon to municipal recycling facilities, our clients trust us to turn recycling data into actionable insights. Our technology has been recognized as one of TIME's Best Inventions and featured in a TIME documentary, TechCrunch, Fortune, and CBS.

The Role:

We're looking for a strong technical leader to own Glacier's Computer Vision strategy and lead our Computer Vision engineering team. This is a hands-on leadership role managing a distributed team across the US and internationally.

Computer Vision is the foundation of our products and plays a pivotal role in the company's success. This role reports directly to the co-founder and CTO.

What you’ll do:
• Own the vision, strategy, and execution of Glacier's Computer Vision roadmap
• Lead and develop our distributed Computer Vision engineering team (hiring, onboarding, performance management across time zones)
• Collaborate cross-functionally with Sales, Operations, and founders to align the Computer Vision roadmap with company strategy and customer needs
• Serve as the technical lead for critical, AI-centric customer projects

Your First 90 Days:
• Own and communicate the Computer Vision roadmap (next 6 months of priorities and technical risks)
• Develop deep system knowledge across our entire ML stack (which models run where and why)
• Understand team strengths, career goals, and performance dynamics
• Assess team capabilities and capacity (what's in our wheelhouse vs. what requires hiring)

Requirements
• 8+ years of professional experience
• 2+ years managing engineering teams of 4+ people
• 2+ years of Computer Vision experience
• Demonstrated track record defining and implementing roadmaps 1+ years out that incorporate experimental R&D
• Firsthand experience training Computer Vision models
• Experience at early-stage startups (