Glacier is a Series A startup based in San Francisco that builds in-house computer vision models to power two core products: a robot that identifies and sorts materials inside recycling facilities, and an analytics system that tracks recyclables and reports metrics to key stakeholders in the industry.
These technologies are already helping to divert tons of recyclables from landfills every day.
The company is expanding its machine learning team based in San Francisco and Latin America by hiring two talented ML Engineers.
The founders come from Facebook engineering and Bain consulting, and the company is backed by top-tier VCs with extensive technical and industry expertise.
There are several machines in production and a robust pipeline of upcoming deployments.
The role involves training and building computer vision models that power upcoming deployments, as well as building the infrastructure and tools to enable faster progress.
Requirements:
Candidates must have 2+ years of experience developing machine learning models in a deep learning framework like Tensorflow/Keras or Pytorch.
Computer vision model development, especially object detectors, is a MUST.
Experience with building machine learning infrastructure, including training pipelines, hyperparameter tuning, and experiment tracking, is required.
Strong expertise in Python and hands-on experience with SQL databases are necessary.
Proficiency with the SciPy ecosystem (numpy, pandas, matplotlib) and distributed computing in frameworks such as Ray is essential.
English fluency is required, as the candidate will be working with a US-based team (B2 or higher).
Experience working with US companies or clients is a plus.
Benefits:
The position offers the opportunity to work fully remote, specifically for candidates based in Latin America.
Employees will be part of a dynamic and innovative team that is making a significant impact in the recycling industry.
The role provides the chance to work with cutting-edge technologies and contribute to game-changing products.
Candidates will have the opportunity to collaborate with experienced professionals from top-tier backgrounds in engineering and consulting.