Glacier

Computer Vision DATA Engineer - Fully Remote USD - Latin America based

Remote Latin America based · Buenos Aires, Argentina

Open 3 months, first seen by us 102 days ago

Pay: $2,000–3,500/month — pay source
Compensation & Benefits $2,000-$3,500 per month/depending on your experience and interview performance 15 Days Paid Time Off + your National Holidays
Read the full posting
Work setting: Remote — work setting source
This role is FULLY REMOTE from Latin America - Pacific Time zone Hey, we're Glacier! A 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.
Location type: Remote
From the employer’s posting
Employment: Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team: Engineering › Machine Learning — team source
Department: Engineering › Machine Learning
From the employer’s posting
Apply by: 18 Nov 2026, 05:00 UTC — apply by source
Application deadline: 2026-11-18T05:00:00.000Z
From the employer’s posting

What you’ll work on

Full posting

Own the image and video dataset lifecycle: taxonomy, curation, collection, and quality
Design and maintain data pipelines for moving, transforming, versioning and syncing datasets
Build internal tools that speed up dataset creation, labeling and curation
Coordinate with the labeling team to keep annotations consistent and error-free
Improve training data collection and prioritization, including model-assisted and active learning

From the employer’s posting

Own our image and video dataset lifecycle: taxonomy, curation, collection workflows, and quality

Design and maintain the data pipelines that move, transform, version, and sync our datasets

Build internal tools and software that make dataset creation, labeling, and curation faster and more reliable

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

What you’ll bring

All qualifications

Core experience

2+ years of Machine Learning experience
Experience with annotation platforms (Supervisely, CVAT, Label Studio) and data versioning tools (DVC).
2+ years building software applications or internal tools, with strong expertise in Python.
Experience with cloud storage (S3) and building backend services (FastAPI).
2+ years of experience working with image or video datasets.
Experience integrating open-source tooling and contributing to internal platforms.

Qualification wording

2+ years of Machine Learning experience

Experience with annotation platforms (Supervisely, CVAT, Label Studio) and data versioning tools (DVC).

2+ years building software applications or internal tools, with strong expertise in Python.

Experience with cloud storage (S3) and building backend services (FastAPI).

2+ years of experience working with image or video datasets.

Experience integrating open-source tooling and contributing to internal platforms.

Benefits in the posting

Full benefits wording

$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

From the employer’s posting.

Apply at Glacier

Posting record

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Open 3 monthsWe first saw this posting 102 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: Jul 28, 2026102 days ago
Recorded sightings: 47
Last seen by us: Nov 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 102

Up longer than most. Similar jobs usually come down between day 6 and day 54.

From 11,471 similar postings that came down. Coming down is not always a hire.

Glacier is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
S3
Django
FastAPI
React

Where the posting names them

- 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).

- 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.

- 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).

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

This role is FULLY REMOTE from Latin America - Pacific Time zone

Hey, we're Glacier! A 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.

Here's where your expertise comes into play:

We're looking for a talented computer vision data engineer to own the data layer that powers our computer vision models. Great models start with great data, and you'll build the datasets, pipelines, and internal tools that let our ML team move fast and train on high-quality, well-curated data. This is a strong fit for someone who loves building software and internal tools as much as working with data..

Your 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.

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).

Nice to have:

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.

Compensation & 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

Why Join Us?

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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