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Remote AI Infrastructure Jobs
Verified remote roles in AI infrastructure — GPU systems, ML serving platforms, cloud architecture, and scalable distributed AI engineering.
AI infrastructure roles on RemoteAI focus on the platforms that make production AI possible. Companies here need engineers who can build ML serving layers, manage GPU compute, design scalable cloud architectures, and keep AI systems reliable as usage grows. These are positions where infrastructure is the core engineering challenge.
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Posted 2 hours ago
AI Resident UK/EMEA
Full-time
English
About EmaEma builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboa...
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Posted 3 hours ago
Senior Product Security Engineer
senior
Full-time
English
About our CompanyAt Hyperscience, we believe that behind every document is a meaningful human experience, whether that’s a family applying for their m...
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Posted 4 hours ago
Devops Engineer, US
Full-time
English
About EmaEma builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboa...
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Posted 4 hours ago
Senior Site Reliability Engineer (SRE)
senior
Full-time
English
About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that suppo...
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Posted 6 hours ago
Infrastructure Engineer
Full-time
English
About ElicitElicit is an AI research assistant that uses language models to help researchers figure out what’s true and make better decisions, startin...
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Posted 8 hours ago
Site Reliability Engineer
Full-time
English
Who we areHelsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societi...
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Posted 9 hours ago
Software Engineer, Hermes Cloud
Full-time
English
The RoleAs a Software Engineer on the Hermes Cloud team, you'll own full-stack engineering across the cloud platform that powers Hermes Agent and Nous...
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Posted 12 hours ago
Senior HPC Engineer, GPU Compute
senior
Full-time
English
About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that suppo...
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Posted 13 hours ago
DevOps Engineer - Platform Integrations
Full-time
English
About TensorWaveOur mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform t...
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Posted 14 hours ago
Senior Staff Infrastructure Engineer - Virtualization
staff
Full-time
English
About TensorWaveOur mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform t...
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FAQ
What is an AI infrastructure job?
AI infrastructure jobs involve designing, building, and scaling the systems that run AI models in production. This includes GPU cluster management, ML serving layers, distributed training infrastructure, cloud architecture, and the platform tooling that AI teams depend on.
How is AI infrastructure different from MLOps?
AI infrastructure roles tend to focus on the underlying compute and platform layer — GPU provisioning, serving infrastructure, networking, and scalability. MLOps roles are more focused on the model lifecycle — pipelines, monitoring, and retraining. In practice, many companies combine these responsibilities.
What skills do AI infrastructure engineers need?
Strong candidates typically have experience with Kubernetes, GPU infrastructure (NVIDIA CUDA), distributed systems, cloud platforms, and high-performance computing. Familiarity with ML serving frameworks like Triton or vLLM is increasingly valuable for senior roles.
What is the salary range for remote AI infrastructure roles?
Remote AI infrastructure engineers typically earn $110K–$180K/year. Roles requiring GPU cluster management or distributed training experience at scale often reach $160K–$210K at well-funded AI labs and startups.
Are AI infrastructure jobs growing?
Yes — significantly. As more companies run large models in production, demand for engineers who can build reliable, cost-efficient AI infrastructure is growing faster than supply. RemoteAI curates these roles specifically for candidates with the right infrastructure background.
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