Engineering Manager, Computer Vision

Glacier•San Francisco, CA

4d•$196,000 - $220,000•Hybrid

About The Position

Glacier is a Series A startup based in San Francisco focused on solving the problem of recyclables ending up in landfills. They build custom sorting robots and AI-powered business analytics to improve recycling processes. Their technology has received recognition from TIME, TechCrunch, Fortune, and CBS. This role is hybrid and requires being in the office on Tuesdays and Thursdays.

Requirements

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

Nice To Haves

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

Responsibilities

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