Remote positions
Browse vetted remote Kubernetes positions — AI infrastructure, MLOps platforms, GPU cluster orchestration, and model serving at scale.
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Kubernetes, docker, and aws spend reports are the core of what we build. If you've ever watched a load test rack up a five-figure cloud bill overnight...
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You'll be the third infrastructure engineer on a team of twelve, working directly with our SRE lead on a tool most engineers wish existed years ago. W...
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Our data pipelines are growing faster than our review process, and models have started reaching production without every required sign-off. This contr...
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The models you'll ship will be used by fleets running 50,000 trips a week across long-haul routes. Fatigue-related incidents cost our customers more t...
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We just closed our Series A and are scaling fast, which means our training checkpoints are growing faster than our storage budget can absorb. We need...
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Git, large monorepos, and a fastapi-based suggestion service are the core of what we build. If you've ever watched a senior engineer burn an afternoon...
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Have you ever shipped a model update to one region only to have a customer in another region hit the stale version for six extra hours because sync si...
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Our palletizing robots misjudge box orientation about once every four hundred cycles, and that one miss costs a line ten minutes of downtime. We're lo...
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Kafka, Spark, and Kubernetes are what we build on every day. If duplicate event storms in a distributed system sound like a fun problem, keep reading....
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Posted 2 months ago
United States — Denver (UTC-6)
Kubernetes, Docker, and AWS are the tools you'll touch every single day here. Our inference clusters scale up and down constantly, and right now that...
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Role guide
Kubernetes is the standard infrastructure platform for production AI systems at scale. Remote Kubernetes jobs at AI companies involve GPU node pool management, MLOps platform engineering, and autoscaling model serving. These roles sit at the intersection of cloud infrastructure and ML systems.
What Kubernetes roles are available remotely in AI?
Primarily MLOps platform engineering, AI infrastructure, and model serving roles. These positions require strong Kubernetes fundamentals plus ML-specific tooling knowledge (Kubeflow, KServe, GPU scheduling).
Do remote Kubernetes AI jobs require cloud provider experience?
Almost always. EKS (AWS), GKE (Google Cloud), and AKS (Azure) are the most common managed Kubernetes platforms. Most job listings specify a primary cloud provider.
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