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On Call Kernel Developer Jobs (NOW HIRING)

Cavallo Solutions

Software Developer II

Grand Rapids, MI · On-site

Participating in a rotating on-call schedule (roughly one week out of eight) as part of our shared ... You have experience configuring or working with LLM-based agents (e.g., LangChain, semantic kernel ...

Cavallo Solutions

Software Developer II

Grand Rapids, MI · On-site

Participating in a rotating on-call schedule (roughly one week out of eight) as part of our shared ... You have experience configuring or working with LLM-based agents (e.g., LangChain, semantic kernel ...

Samsung

Senior Linux/Unix Engineer

Moonachie, NJ

Perform off-hours maintenance as required and on-call support. Develop/detail technical ... Knowledge of the Linux kernel and kernel modules Familiarity with open source tools, monitoring ...

Samsung

Senior Linux/Unix Engineer

Moonachie, NJ · On-site

... on-call support. • Develop/detail technical specifications and provide technical direction ... Linux kernel and kernel modules • Familiarity with open source tools, monitoring systems • ...

Jobsbridge

Site Reliability Engineer

San Francisco, CA

$67.25 - $89.25/hr

Participate in periodic on call duties. Represent the SRE team in design reviews and operational ... Experience working with Unix/Linux systems from kernel to shell and beyond, with experience working ...

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On Call Kernel Developer information

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How much do on call kernel developer jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for on call kernel developer in the United States is $54.42, according to ZipRecruiter salary data. Most workers in this role earn between $47.12 and $61.54 per hour, depending on experience, location, and employer.

What is the difference between On Call Kernel Developer vs System Administrator?

AspectOn Call Kernel DeveloperSystem Administrator
CredentialsKnowledge of Linux/Unix, programming skills, sometimes certifications like Linux FoundationCertifications like CompTIA Server+, Microsoft Certified, Linux certifications often preferred
Work EnvironmentPrimarily technical, focused on kernel and system-level issues, often in data centers or development labsOperational, managing servers, networks, and user support in office or data center settings
Industry UsageTech companies, data centers, cloud providersIT departments across various industries, including finance, healthcare, and education
Search & Comparison IntentTechnical troubleshooting, kernel development, system stabilitySystem maintenance, user support, network management

The main difference is that On Call Kernel Developers focus on low-level system code and kernel issues, often working in technical environments, while System Administrators handle broader system management and user support. Both roles require technical skills but differ in scope and focus.

More about On Call Kernel Developer jobs
What are the most commonly searched types of Kernel Developer jobs? The most popular types of Kernel Developer jobs are:
What job categories do people searching On Call Kernel Developer jobs look for? The top searched job categories for On Call Kernel Developer jobs are:
On Call Kernel Developer jobs near you
Infographic showing various On Call Kernel Developer job openings in the United States as of August 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 78% Full Time, 14% Part Time, and 6% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $113,185 per year, or $54.4 per hour.

Senior Staff+ Software Engineer, Node Infra

Anthropic

San Francisco, CA • On-site

$144K - $190K/yr

Full-time

Re-posted 15 days ago

Job description

About the role

Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users - demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.

Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major cloud providers and from datacenters custom-built for Anthropic, stand up and scale the clusters behind one of the industry's largest AI compute fleets, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic's frontier AI research.

Key responsibilities
  • Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair
  • Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families
  • Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity
  • Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others
  • Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy
  • Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)
  • Support the growth of engineers around you through technical mentorship and coaching
Minimum qualifications
  • Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
  • Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform.
  • Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium)
  • Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems
  • Ability to build alignment across senior stakeholders and communicate effectively at all levels
Preferred qualifications
  • 12+ years of software engineering experience, including time as a technical lead setting direction for a team
  • Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency
  • Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines
  • Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons
  • Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads.
  • Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems
  • Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.)
  • Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems

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