Remote positions
Browse vetted remote Kubernetes positions — AI infrastructure, MLOps platforms, GPU cluster orchestration, and model serving at scale.
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Full-time roles and fixed-scope freelance missions — matched to your AI skills.
Docker, Kubernetes, and MLflow are the core of what we build at Lumio Systems. If you've shipped model deployments that engineering teams actually tru...
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Posted 3 months ago
United States — Los Angeles (UTC-7)
You'll be the second infrastructure specialist on a lean four-person platform team, working directly with our CTO to solve a problem that's been quiet...
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The autoscaling decisions you'll make will directly control GPU spend for over 40 enterprise clients running models on our deployment platform. Right...
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PyTorch models, Kubernetes clusters, and a serverless inference layer are what our platform runs on today, but edge deployments are where our biggest...
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Our QA platform already generates synthetic test data and tracks test coverage, but flaky tests still waste hours of engineering time every week acros...
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Have you ever watched a feature rollout go sideways because nobody caught the early warning signs in time? Our deployment platform already handles con...
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Have you ever pushed a serverless ML function update at 5pm on a Friday and spent the whole weekend manually rolling it back after it started throwing...
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Posted 3 months ago
United States — Los Angeles (UTC-7)
You'll be the fourth infrastructure engineer on a team of 14, working alongside platform, ML, and SRE. We already run large-scale model training and i...
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Have you ever wondered why two deployments running the same model cost wildly different amounts per request? We run model deployments across dozens of...
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You'll be the fourth infrastructure engineer on a team of eleven, reporting into our platform lead. We already have solid deployment reliability tooli...
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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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