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Engineering Manager, Computer Vision

GlacierSoftware
Pay
$196K–$220K
per year
Work mode
Hybrid
Full Time
Experience
2+ yrs
Senior

San Francisco, CA at a glance

Rent
#2 of 51
$2,680/mo+46% vs US avg
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295 mild days0 hot · 0 cold
Income tax
#1 of 51
13.3% top rateCalifornia

What you need

  • 2+ yrs engineering management experience
  • 2+ yrs hands-on computer vision / ML engineering
  • Experience training and deploying CV models
  • Intermediate Python and SQL proficiency
  • Experience building technical roadmaps

What you'll do

  • Own CV roadmap vision and execution
  • Lead and mentor distributed CV engineering team
  • Set project priorities and unblock engineers
  • Provide technical guidance on models and datasets
  • Partner with cross-functional teams

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


About Glacier

Hey, we're Glacier! 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 an experienced Engineering Manager, Computer Vision to lead Glacier's Computer Vision organization. You'll own the vision and execution of our CV roadmap, lead our international CV engineering team, and ensure the team is focused on the highest-priority work.

This role reports directly to our Co-Founder and CTO and will play a key role in shaping our computer vision strategy, team execution, and cross-functional collaboration as we scale.

What you'll do

  • Own the vision, strategy, and execution of Glacier's computer vision roadmap in partnership with Product Management

  • Lead, mentor, and develop our distributed CV engineering team, including hiring, performance, upskilling, and retention

  • Set project and task-level priorities, keeping engineers focused and unblocked

  • Break complex technical challenges into clear plans and coordinate execution across multiple engineers and workstreams

  • Provide technical guidance on models, datasets, compute, evaluation, and production performance

  • Establish lightweight processes that improve execution and collaboration

  • Partner with Software, Operations, Manufacturing, and Field Engineering to identify and resolve cross-functional dependencies

  • Oversee the labeling function, including resourcing, budget, and quality

This is a technical leadership role, not a day-to-day development role. You won't be expected to directly code, but you should be comfortable getting deep into technical problems and providing credible guidance on computer vision systems.

What we're looking for

  • 2+ years of engineering management experience

  • 2+ years of hands-on computer vision / ML engineering experience

  • Firsthand experience training and deploying computer vision models

  • Strong technical understanding of model optimization, dataset quality, compute, evaluation, and production performance

  • At least intermediate Python and SQL proficiency

  • Experience building technical roadmaps and coordinating complex, cross-functional projects

What will make you successful

  • Technical depth: You can engage deeply with computer vision problems and guide strong engineers through deeply technical challenges

  • Prioritization: You can turn ambiguous technical challenges into clear priorities and balance team interests with company needs

  • Systems thinking: You understand how your team decisions affect Software, Operations, Manufacturing, Field Engineering, and customers

  • Execution: You break large problems into actionable plans, manage dependencies, and surface risks early

  • Communication: You're concise, can push back thoughtfully, and adjust when new information changes the right answer

  • Leadership: You know how to support and challenge a highly autonomous team while keeping people accountable

Bonus points

  • Experience working in an early-stage startup environment (<50 employees)

  • Industrial automation, robotics, or other real-world physical systems experience

  • ML systems deployed at customer sites

  • Experience managing or working closely with data labeling teams

  • Edge ML or production computer vision experience

Compensation

The total cash compensation range for this role is $196,000 - $220,000. In addition to cash compensation, Glacier also offers competitive equity compensation and benefits. Final compensation will depend on job-related skills and knowledge, experience level, interview performance, and other relevant factors.


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About Glacier

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.

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