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Remote Junior Linux Kernel Engineer Ubuntu Jobs in California

Ventana Micro Systems

Compiler Engineer

Cupertino, CA · On-site +1

$105K - $260K/yr

San Francisco Bay Area, Cupertino, or Fully Remote Position: Compiler Engineer Status: Full time ... Linux application and kernel performance optimization - knowledge of perf, oprofile, flame graphs ...

Xage Security

Senior Backend Engineer

Palo Alto, CA · Remote

$150K - $180K/yr

... Remote Access Named in Forrester research on Operation Technology Security Solutions, and ... Strong communication skills and expert system level skills on Linux OS such as Ubuntu, Alpine, Red ...

Peraton

DevOps/ Platform Engineer

San Diego, CA · On-site +1

$80K - $128K/yr

This hybrid support role (75% remote, 25% onsite at a government facility) in the San Diego area is ... Linux systems (e.g., RHEL, CentOS, Ubuntu) * Automation and scripting (e.g., Bash, Python ...

Peraton

DevOps/ Platform Engineer

San Diego, CA · On-site +1

$80K - $128K/yr

This hybrid support role (75% remote, 25% onsite at a government facility) in the San Diego area is ... Linux systems (e.g., RHEL, CentOS, Ubuntu) * Automation and scripting (e.g., Bash, Python ...

Peraton

Senior DevOps / Platform Engineer

San Diego, CA · On-site +1

$104K - $166K/yr

This hybrid support role (75% remote, 25% onsite at a government facility) in the San Diego area is ... Linux systems (e.g., RHEL, CentOS, Ubuntu) * Automation and scripting (e.g., Bash, Python ...

Peraton

Senior DevOps / Platform Engineer

San Diego, CA · On-site +1

$104K - $166K/yr

This hybrid support role (75% remote, 25% onsite at a government facility) in the San Diego area is ... Linux systems (e.g., RHEL, CentOS, Ubuntu) * Automation and scripting (e.g., Bash, Python ...

Mettle

Laravel Engineer (Remote)

San Francisco, CA · On-site +1

As part of the Engineering team, your time will be spent collaborating with other engineers and ... Server admin (Ubuntu, ngninx, Forge, Envoyer, Docker) * AWS, Google Cloud, Digital Ocean

IDT

Senior/Lead VoIP (Asterisk) Engineer

San Jose, CA · On-site +1

Work with Linux systems (systemd, networking, tuning, kernel parameters). * Work with Asterisk in ... Remote b2b (Georgia-Moldova) or on-site employment (Belarus-Moldova) work opportunity! * Stable job ...

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All JobsLinux Kernel Engineer Ubuntu JobsRemote Junior Linux Kernel Engineer Ubuntu JobsRemote Junior Linux Kernel Engineer Ubuntu Jobs in California

Remote Junior Linux Kernel Engineer Ubuntu information

What is the difference between Remote Junior Linux Kernel Engineer Ubuntu vs Remote Junior Linux System Administrator?

AspectRemote Junior Linux Kernel Engineer UbuntuRemote Junior Linux System Administrator
Primary FocusDeveloping and optimizing Linux kernel components on UbuntuManaging, configuring, and maintaining Linux systems and servers
Required SkillsLinux kernel development, C programming, Ubuntu environmentLinux system setup, scripting, troubleshooting, Ubuntu/Debian familiarity
CertificationsLinux Foundation Certified Engineer, Kernel development coursesLPIC-1, CompTIA Linux+, Ubuntu certifications
Work EnvironmentDevelopment teams, Linux kernel projects, Ubuntu-based systemsIT support, system administration, server management

While both roles involve Linux and Ubuntu, the Remote Junior Linux Kernel Engineer Ubuntu focuses on kernel development and optimization, whereas the Remote Junior Linux System Administrator handles system maintenance and support. The former requires programming and kernel knowledge, while the latter emphasizes system management skills.

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Infographic showing various Remote Junior Linux Kernel Engineer Ubuntu job openings in California as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Member of Technical Staff - GPU Infrastructure

Prime Intellect

San Francisco, CA • On-site, Remote

$150/hr

Full-time

Posted 21 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.
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.
Core Technical Responsibilities
This customer-facing role combines deep technical expertise with hands-on implementation. You'll be instrumental in:
Customer Architecture & Design
  • Partner with clients to understand workload requirements and design optimal GPU cluster architectures
  • Create technical proposals and capacity planning for clusters ranging from 100 to 10,000+ GPUs
  • Develop deployment strategies for LLM training, inference, and HPC workloads
  • Present architectural recommendations to technical and executive stakeholders

Infrastructure Deployment & Optimization
  • Deploy and configure orchestration systems including SLURM and Kubernetes for distributed workloads
  • Implement high-performance networking with InfiniBand, RoCE, and NVLink interconnects
  • Optimize GPU utilization, memory management, and inter-node communication
  • Configure parallel filesystems (Lustre, BeeGFS, GPFS) for optimal I/O performance
  • Tune system performance from kernel parameters to CUDA configurations

Production Operations & Support
  • Serve as primary technical escalation point for customer infrastructure issues
  • Diagnose and resolve complex problems across the full stack - hardware, drivers, networking, and software
  • Implement monitoring, alerting, and automated remediation systems
  • Provide 24/7 on-call support for critical customer deployments
  • Create runbooks and documentation for customer operations teams

Technical Requirements
Required Experience
  • 3+ years hands-on experience with GPU clusters and HPC environments
  • Deep expertise with SLURM and Kubernetes in production GPU settings
  • Proven experience with InfiniBand configuration and troubleshooting
  • Strong understanding of NVIDIA GPU architecture, CUDA ecosystem, and driver stack
  • Experience with infrastructure automation tools (Ansible, Terraform)
  • Proficiency in Python, Bash, and systems programming
  • Track record of customer-facing technical leadership

Infrastructure Skills
  • NVIDIA driver installation and troubleshooting (CUDA, Fabric Manager, DCGM)
  • Container runtime configuration for GPUs (Docker, Containerd, Enroot)
  • Linux kernel tuning and performance optimization
  • Network topology design for AI workloads
  • Power and cooling requirements for high-density GPU deployments

Nice to Have
  • Experience with 1000+ GPU deployments
  • NVIDIA DGX, HGX, or SuperPOD certification
  • Distributed training frameworks (PyTorch FSDP, DeepSpeed, Megatron-LM)
  • ML framework optimization and profiling
  • Experience with AMD MI300 or Intel Gaudi accelerators
  • Contributions to open-source HPC/AI infrastructure projects

Growth Opportunity
You'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.
We value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.
Apply now and join us in our mission to democratize access to planetary scale computing.
Compensation
Cash Compensation Range of $150-300k plus Equity Incentives

Apply