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Remote Apache Airflow Jobs
Browse remote Airflow positions at companies running production ML pipelines — DAG engineering, workflow orchestration, and MLOps automation roles.
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The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across t...
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Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a b...
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Posted 3 weeks ago
Staff Applied AI Engineer - Enterprise AI Solutions
New York City, NY (Hybrid); San Francisco, CA (Hybrid); United States (Remote)
Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine techn...
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Owkin is an agentic AI company pioneering Biological Artificial Superintelligence to solve problems in biology where human researchers alone have fail...
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Prefect builds automation for an unpredictable world. The last decade of automation was about protecting workflows from unpredictability; in the agent...
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Posted 3 weeks ago
Staff Software Engineer, Platform Infrastructure
London · also open in 2 other locations
Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading uni...
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Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading uni...
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At Pika, we’re building the next generation of AI creative tools to empower human creativity. Our mission is to make video creation seamless, intuitiv...
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Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows,...
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Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a b...
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Role guide
What to expect in remote Airflow jobs
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 you'll work on
- Build Airflow DAGs that automate ML model retraining on schedule or data trigger
- Orchestrate multi-step pipelines across Spark, dbt, and ML systems
- Monitor and alert on pipeline failures in production data workflows
- Migrate fragile cron jobs to reliable, retryable Airflow workflows
What companies look for
- Production DAG design — modularity, testing, failure handling
- Airflow operator, sensor, and hook development experience
- Knowledge of Airflow deployment on Kubernetes or Astronomer
Frequently asked questions
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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