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Remote Infrastructure Engineer Jobs in Dublin, CA

Figma

Support Engineer, AI Infrastructure

San Francisco, CA · On-site +1

$126K - $166K/yr

As a Support Engineer, AI Infrastructure on this team, you'll be the technical execution layer that brings our support tools, customer and account context, internal systems, and AI workflows together.

Humble Robotics

ML Infra Engineer

San Francisco, CA · Remote

$110K - $144K/yr

Position Overview We're looking for an ML infrastructure engineer to help design, build, and scale the foundational systems we need to realize our ambitious vision. You'll work on tooling and ...

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Remote Infrastructure Engineer information

See Dublin, CA salary details

$52.4K

$143.1K

$205K

How much do remote infrastructure engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote infrastructure engineer in Dublin, CA is $143,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,100.00 and $158,800.00 per year, depending on experience, location, and employer.

What is a remote infrastructure engineer?

A Remote Infrastructure Engineer is responsible for designing, managing, and maintaining an organization's IT infrastructure, including servers, networks, cloud environments, and security systems, while working remotely. They ensure system reliability, optimize performance, troubleshoot issues, and implement new technologies to support business operations. This role requires expertise in networking, cloud computing, automation, and cybersecurity, often working with tools like AWS, Azure, VMware, and monitoring systems. Effective communication and problem-solving skills are essential, as they collaborate with teams to resolve technical challenges.

What does a remote infrastructure engineer do?

As a Remote Infrastructure Engineer, your daily responsibilities generally include monitoring system performance, deploying updates and patches, managing cloud resources, and troubleshooting network or server issues. You'll often work closely with development and security teams to ensure optimal infrastructure performance, automate routine processes, and uphold security standards. Collaboration through project management platforms and remote communication tools is common to keep the team aligned. The role frequently involves both scheduled maintenance and responding to urgent incidents, offering a dynamic and impactful work environment.

What skills and qualifications are needed to be a remote infrastructure engineer?

To thrive as a Remote Infrastructure Engineer, you need a strong background in network administration, cloud computing, and server management, often paired with a degree in computer science or related field. Familiarity with tools like AWS, Azure, Docker, Kubernetes, and certifications such as AWS Certified Solutions Architect or CompTIA Network+ are typically expected. Excellent problem-solving abilities, proactive communication, and strong organizational skills help you manage tasks independently and collaborate across dispersed teams. These capabilities are crucial for maintaining reliable, secure infrastructure and supporting seamless remote operations for organizations.

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Remote Infrastructure Engineer jobs near you

Research Engineer - RL Infrastructure

Prime Intellect

San Francisco, CA • On-site, Remote

$350K/yr

Full-time

Re-posted 27 days ago

Job description

Own Your Intelligence
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.
We train open frontier models and ship the same stack to our customers. Its spans the full stack of training, deploying and continuously improving models - compute, large-scale RL, environments, sandboxes, evals, and deployment.
Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators - including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.
What You'll Work On
  • Build and optimize the systems infrastructure behind large-scale RL and distributed training workloads by contributing to our prime-rl framework.
  • Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers.
  • Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements.
  • Work on distributed training systems spanning data, tensor, and pipeline parallel workloads.
  • Help shape the architecture of our RL training stack, including async rollout and post-training systems.
  • Contribute to open-source libraries and internal infrastructure used for frontier-scale model training.
  • Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements.
  • Stay at the frontier of training systems, inference systems, compiler/runtime tooling, and hardware-aware optimization techniques.

You May Be a Fit If You Have
  • Strong systems engineering experience in AI/ML infrastructure, especially around large-scale model training or inference.
  • Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP, Megatron, vLLM, Ray, or related tooling.
  • Experience optimizing training performance across kernels, memory movement, communication overhead, or parallelization strategy.
  • Hands-on experience with large-scale training techniques including data parallelism, tensor parallelism, and pipeline parallelism.
  • Strong understanding of GPU architecture, profiling, and performance debugging.
  • Ability to identify bottlenecks across the stack and drive improvements from first principles.
  • Comfort working in a fast-moving environment with ambiguous problems and high ownership.

Especially Exciting
  • Experience writing or optimizing CUDA / Triton kernels.
  • Experience with compiler or runtime optimization for ML systems.
  • Experience working on RL training infrastructure, rollout systems, or asynchronous training pipelines.
  • Experience with multi-node GPU clusters and high-performance networking.
  • Contributions to open-source ML systems or infrastructure projects.
  • Interest in publishing technical work or sharing insights through engineering blogs and technical writing.

Why This Role Matters
The next frontier in AI will not be unlocked by models alone. It will be unlocked by systems that let those models train faster, adapt continuously, and operate across real environments at scale.
That infrastructure does not exist yet in the form the world needs.
We're building it.
Benefits & Perks
  • Cash Compensation Range of $150-350k, plus equity.
  • Flexible work arrangements, with the option to work remotely or in person from our San Francisco office.
  • Visa sponsorship and relocation support for international candidates.
  • Quarterly team offsites, hackathons, conferences, and learning opportunities.
  • A deeply technical, high-agency team working on infrastructure for open superintelligence.

If you're excited about building the systems foundation for frontier-scale RL and open superintelligence, we'd love to hear from you.

Apply