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Browse remote Airflow positions at companies running production ML pipelines — DAG engineering, workflow orchestration, and MLOps automation roles.
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Posted 5 months ago
Applications closedGlyph Systems
Remote
Chicago, United States (UTC-6)
Government agencies publish vast amounts of data — court records, permit filings, inspection reports, budget documents — but each one in a different f...
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Posted 5 months ago
Applications closedCovex Cloud
Remote
Chicago, United States (UTC-6)
When a company spends $200K per month on cloud AI services, the CFO wants to know which team, which project, and which model consumed what. Our cost a...
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Posted 5 months ago
Applications closedUnvix Works
Remote
New York, United States (UTC-5)
We connect AI models to business processes for mid-market companies. Not the sexy part of AI — the plumbing. Data flows in, gets transformed, hits a m...
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Posted 5 months ago
Applications closedCandor Systems
Remote
New York, United States (UTC-5)
We run the inference backbone for 14 mid-market SaaS companies. They build the apps — we keep their models serving, scaling, and not falling over at 3...
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Posted 5 months ago
Applications closedVelmox Data
Remote
New York, United States (UTC-5)
Feature engineering is where most ML projects succeed or fail, and most teams do it badly. Features get copy-pasted between notebooks, computed differ...
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Posted 5 months ago
Applications closedLyrex Data
Remote
Berlin, Germany (UTC+1)
Data teams waste 30% of their time just finding the right dataset. Our data catalog uses AI to automatically profile, tag, and document every table, c...
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Posted 5 months ago
Applications closedNortex Solutions
Remote
Chicago, United States (UTC-6)
Insurance companies process 200,000 claims per month, and each claim involves 8-15 documents: medical records, police reports, repair estimates, polic...
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Posted 5 months ago
Applications closedJoltura Labs
Remote
New York, United States (UTC-5)
Shipping ML models to production should be as boring as deploying a web app. At most companies, it isn't — releases take days, rollbacks are manual, a...
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Posted 5 months ago
Applications closedInfera Cloud
Remote
Los Angeles, United States (UTC-8)
Every ML model is only as good as its data, and ours processes 800GB daily from IoT sensors deployed across 200 wind farms. Turbine vibration data, we...
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Posted 5 months ago
Applications closedQuelva Works
Remote
Chicago, United States (UTC-6)
Our clients are mid-size law firms drowning in repetitive document work — contract review, due diligence, regulatory filings. They've tried hiring mor...
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Role guide
Apache Airflow is the most widely deployed ML pipeline orchestration tool. Remote Airflow jobs involve designing maintainable DAGs, integrating Airflow with cloud data infrastructure, and ensuring ML training pipelines run reliably. Engineers with Airflow experience plus ML system knowledge are in consistent demand.
What Airflow roles are available remotely?
Primarily data engineering and MLOps roles where Airflow is part of the orchestration stack. Pure "Airflow engineer" titles are rarer — most roles combine Airflow with Python, cloud platforms, and data tools like dbt or Spark.
Do remote Airflow jobs require Kubernetes experience?
Increasingly yes. KubernetesExecutor and Astronomer deployments are common at scale. Smaller companies may use CeleryExecutor or LocalExecutor — check individual job listings for infrastructure specifics.
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