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.
Posted 5 months ago
United States — New York (UTC-4)
This is the role for someone who is a little tired of hearing about AI strategy and a lot more interested in why the deployment failed at 2:13 a.m. Ou...
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We need a contractor who can come in, assess a messy but functioning ML stack, and help us move it onto more reliable infrastructure without turning t...
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Our research and applied ML teams move quickly, but the training stack around them is inconsistent and expensive. We need a platform engineer to stand...
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We are a government technology agency based in Singapore. We build and operate the digital infrastructure and citizen-facing services for the Singapor...
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Posted 5 months ago
United States — New York (UTC-4)
We build software used by clinical operations teams to review, summarise, and route visit documentation. The models are important, but reliability is...
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About the role: we are hiring a Senior MLOps Engineer to join the core platform team behind our AI observability product. Our customers run production...
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ML Platform Engineer needed for a biotech software environment supporting molecular diagnostics workflows. The platform needs stronger standardisation...
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Posted 5 months ago
United Kingdom — London (UTC+1)
This role sits within the data and AI directorate of a UK central government department. Our team is responsible for the infrastructure that runs mach...
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Posted 5 months ago
United States — New York (UTC-4)
A fintech data platform has accumulated too many one-off feature pipelines and inconsistent lineage. The internal team knows what needs to be cleaned...
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We are the company behind an open source ML experiment tracking and model registry tool with 9,200 GitHub stars and a contributor community of 340 peo...
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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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