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 Kingdom — London (UTC+1)
This role sits within the Advanced Driver-Assistance Systems (ADAS) perception team of a Tier 1 automotive supplier. We develop perception stacks for...
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We are a two-sided marketplace for skilled trades — connecting homeowners with vetted electricians, plumbers, and HVAC technicians in 38 metropolitan...
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We are a fully distributed team of 23 people across 11 time zones. We have not held a synchronous all-hands meeting in two years. Every significant de...
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Posted 5 months ago
United States — New York (UTC-4)
We are an enterprise software company headquartered in Bengaluru, India. We have 4,200 engineers, 600 enterprise clients across 34 countries, and a pr...
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We are a payments infrastructure company. We process card-not-present transactions for 3,800 merchants across Europe, with a combined volume of €2.1 b...
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POSITION TYPE: Contract, 12 months initial term with extension subject to programme continuation. CLEARANCE REQUIREMENT: Developed Vetting (DV) or SC...
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We run 20 ML models in production. Some of them are fine. Some of them catch fire in ways that are not always predictable. Our current infrastructure...
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We operate a real-time recommendation system serving 800 million requests per day across 40+ models running in parallel on AWS, with specific workload...
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I want to be honest with you about what we are and what we're not. We are a 400-person company. We have a mature product, a real revenue base, and a d...
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Our researchers are brilliant. Our infrastructure is not. Training runs die halfway through, experiment results get lost, and deployments happen over...
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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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