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 (<50 employees)
Ability to work from our San Francisco office (Dogpatch) at least two days/week
Why Join Us?
Mission-Driven Work – Be part of a company dedicated to sustainability and ending waste, with technology recognized as one of TIME's Best Inventions
AI Leadership – Own the vision and execution of AI that powers real-world robots diverting tons of recyclables from landfills daily.
Global Team – Lead a talented, distributed ML team across the US and internationally.
Fast-Paced Growth – Join at a pivotal moment as we scale deployments nationwide.
Backed to Succeed – Our founders bring experience from Facebook and Bain, supported by top-tier investors.
Compensation:
The total cash compensation range for this role is $175,000 - $250,000. In addition to cash compensation, Glacier also offers competitive equity compensation and benefits. The final compensation for this role will depend on many individualized factors, including job-related skills and knowledge, experience level, interview performance, and other factors.
Other open roles at Glacier(1)
Glacier's mission is to end waste. Sound ambitious? We agree. But the UN estimates that we only have until 2030 to change our consumption patterns before we do irreversible damage to the environment, so we’re of the opinion that now is the time for big bets. We’re starting in the world of recycling, which has a huge opportunity for impact. Americans send 1.4 million tons of waste to recycling facilities every week (that’s about 4 Empire State Buildings, or 1.5 Golden Gate Bridges). We’re also really bad at it: 25% of what we put in our recycling bins isn’t even recyclable. These recycling facilities make a living by sorting our jumbled-up waste and they need to do it cheaply and accurately. Otherwise they go out of business and our recycling goes straight to the landfill. Even so, recycling facilities today use processes that are highly manual, expensive, and error prone. We plan to revolutionize the way these facilities use technology, to make them more streamlined, accurate, and profitable - which means more recyclables avoid the landfill, and more of our natural resources are protected. Our growing team draws from the brightest and most passionate professionals across robotics, manufacturing, software, AI, and market strategy. We’re united by our deep-rooted passion to make a big environmental impact, and we’re looking for other mission-driven, creative thinkers to help us right the ship on this truly global issue.
Key team members
Abe Murray
Ann Bordetsky
Ting Zhang
Rebecca Hu-Thrams
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