Computer Vision Engineer - Fully Remote USD - Latin America based at Glacier

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Computer Vision Engineer - Fully Remote USD - Latin America based at Glacier. Remote Location: San Francisco Office. 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. 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 (literally!) from landfills every day.. We’re thrilled to expand our incredible machine learning team based in San Francisco and Latin America by hiring two talented ML Engineers.. About us:. Our founders come from Facebook engineering and Bain consulting.. We’re backed by top-tier VCs with extensive technical and industry expertise.. We have several machines in production and a robust pipeline of upcoming deployments.. Here's where your expertise comes into play:. We’re looking for a talented machine learning engineer to help us build our game-changing technologies. You will be responsible for training and building the computer vision models that power our upcoming deployments, as well as helping to build the infrastructure and tools to enable us to move faster.. Your responsibilities:. Drive the performance of our ML models. That includes: building ML infrastructure, improving current model performance, fine tuning our training process, and ensuring we can easily collect high quality training data.. Build automation and experimentation into our full ML lifecycle, enabling us to deploy systems and create impact at scale.. Coordinate with our labeling team to ensure we’re working with error-free and well curated data. Requirements:. 2+ years 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 (training pipelines, hyperparameter tuning, experiment tracking, etc).. Strong expertise in Python and hands-on experience in SQL databases.. Proficiency with the SciPy ecosystem (numpy, pandas, matplotlib) and distributed computing in frameworks such as Ray.. English Fluency as you will be working with a US based team (B2 or higher). Experience working with US companies or clients is a plus