glacier - Computer Vision DATA Engineer - Fully Remote USD - Latin America based
Requirements
• 2+ years of Machine Learning experience • 2+ years building software applications or internal tools, with strong expertise in Python. • 2+ years of experience working with image or video datasets. • Hands-on experience designing and maintaining data pipelines (ETL/ELT, workflow orchestration, data versioning). • Strong SQL and experience working with structured data. • English fluency, as you'll be working with a US-based team (B2 or higher). • Computer vision background or experience supporting CV/ML teams. • Web application development (React + Django, Nextjs) • Experience with annotation platforms (Supervisely, CVAT, Label Studio) and data versioning tools (DVC). • Experience with cloud storage (S3) and building backend services (FastAPI). • Experience integrating open-source tooling and contributing to internal platforms. • Experience working with US companies or clients.
Responsibilities
• Own our image and video dataset lifecycle: taxonomy, curation, collection workflows, and quality, so our models train on clean, well-structured, error-free data. • Design and maintain the data pipelines that move, transform, version, and sync our datasets (e.g. DVC, annotation platforms, cloud storage). • Build internal tools and software that make dataset creation, labeling, and curation faster and more reliable for the ML and labeling teams. • Coordinate closely with our labeling team to ensure data is well curated, consistently annotated, and error-free. • Improve how we collect and prioritize training data over time, including model-assisted and active-learning approaches.
Benefits
• $2,000-$3,500 per month/depending on your experience and interview performance • 15 Days Paid Time Off + your National Holidays • $500 for your remote set up + $100/mo for your wellness • Mission-Driven Work – Be part of a company dedicated to sustainability and ending waste. • Cross-Functional Impact – Work closely with product, engineering, field operations, and customer success to solve complex problems with meaningful outcomes. • Backed to Succeed – Our founders bring experience from Facebook and Bain, and we’re supported by top-tier investors with deep technical and industry expertise.
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