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Remote Linux Trainer Jobs in California (NOW HIRING)

Hologic Inc.

Senior Product Security Engineer

Santa Clara, CA · On-site +1

$134K - $184K/yr

... remote connectivity solutions, providing support to product teams as needed. * Risk Management ... Education and Training: Educate sales and service teams on securing our products, connected health ...

IDT

Senior/Lead VoIP (Asterisk) Engineer

San Jose, CA · Remote

Work with Linux systems (systemd, networking, tuning, kernel parameters). * Work with Asterisk in ... Remote work flexibility - work from anywhere. * B2B contract with competitive gross compensation in ...

talentpluto

Research Engineer

San Francisco, CA · Remote

On-site (some team members are remote, but this role is currently on-site) Industry: AI ... Define and enforce quality standards for training datasets used for RL training and evaluation

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Remote Linux Trainer information

What are the key skills and qualifications needed to thrive as a Remote Linux Trainer, and why are they important?

To thrive as a Remote Linux Trainer, you need deep expertise in Linux operating systems, strong instructional abilities, and relevant certifications such as CompTIA Linux+ or Red Hat Certified Engineer (RHCE). Familiarity with virtual training platforms, remote collaboration tools, and lab simulation software is typically required. Excellent communication, patience, and the ability to adapt teaching methods to various learning styles are vital soft skills. These competencies ensure effective remote instruction, learner engagement, and successful knowledge transfer in a virtual environment.

What is the difference between Remote Linux Trainer vs Linux Instructor?

AspectRemote Linux TrainerLinux Instructor
CertificationsLinux Professional Institute (LPIC), CompTIA Linux+LPIC, CompTIA Linux+, RHCSA
Work EnvironmentOnline/remote training sessions, corporate or individual clientsOnline or in-person classrooms, educational institutions
Employer & IndustryTraining companies, tech firms, online education platformsUniversities, colleges, training centers
Search & Comparison IntentYesYes

The main difference between a Remote Linux Trainer and a Linux Instructor lies in their typical work settings and target audiences. Remote Linux Trainers often focus on online, flexible training for corporate clients or individual learners, while Linux Instructors may work in traditional classroom environments within educational institutions. Both roles require similar certifications and technical expertise, but their work environments and delivery methods differ.

How does a Remote Linux Trainer typically structure interactive learning and support for students in a virtual environment?

As a Remote Linux Trainer, you will often use a blend of live online sessions, pre-recorded tutorials, and hands-on lab exercises to engage students. Interactive elements like real-time Q&A, virtual breakout rooms, and collaborative troubleshooting are common to ensure learners stay involved and can practice their skills. Trainers also provide ongoing support through forums, chat, or scheduled virtual office hours, making it crucial to be proactive and responsive to student needs. This structure requires trainers to be comfortable with various e-learning platforms and to adapt their teaching style for remote delivery.

What does a Remote Linux Trainer do?

A Remote Linux Trainer is responsible for teaching individuals or groups how to use and administer the Linux operating system from a remote location, usually via online platforms. They develop and deliver instructional materials, lead virtual labs, and provide support to learners with varying levels of experience. Their goal is to help students acquire practical Linux skills for personal or professional use, often preparing them for certifications or workplace requirements.
What are popular job titles related to Remote Linux Trainer jobs in California? For Remote Linux Trainer jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Linux Trainer jobs in California look for? The top searched job categories for Remote Linux Trainer jobs in California are:
What cities in California are hiring for Remote Linux Trainer jobs? Cities in California with the most Remote Linux Trainer job openings:
Remote Linux Trainer jobs near you

Senior Site Reliability Engineer - AI Infrastructure

Andromeda Cluster, Inc

San Francisco, CA • On-site, Remote

$67.25 - $89.25/hr

Full-time

Posted 17 days ago

Job description

Senior Site Reliability Engineer - AI Infrastructure
Location: Global Remote / San Francisco • Full-Time
About Andromeda
Andromeda Cluster was founded by Nat Friedman and Daniel Gross to give early-stage startups access to the kind of scaled AI infrastructure once reserved only for hyperscalers.
We began with a single managed cluster - but it filled almost instantly. Since then, we've been quietly building the systems, network, and orchestration layer that makes the world's AI infrastructure more accessible.
Today, Andromeda works with leading AI labs, data centers, and cloud providers to deliver compute when and where it's needed most. Our platform routes training and inference jobs across global supply, unlocking flexibility and efficiency in one of the fastest-growing markets on earth.
Our long-term vision is to build the liquidity layer for global AI compute - a marketplace that moves the infrastructure and workloads powering AGI not dissimilar to the flows of capital in the world's financial markets.
We are expanding to new frontiers to find the brightest that work in AI infrastructure, research and engineering.
The Role
This is not a generalist SRE role.
You will design, operate, and debug large-scale GPU infrastructure used for distributed training and inference, working directly with customers pushing the limits of modern AI systems.
We're looking for engineers who have personally run GPU clusters in production, understand the failure modes of distributed training, and can reason about performance from network fabric → kernel → framework.
What You'll Own
  • GPU Cluster Architecture: Design and evolve multi-provider, multi-region GPU compute clusters optimized for large-scale training. Make topology-aware scheduling, networking, and storage decisions that directly impact training throughput and cost efficiency.
  • Customer Technical Partnership: Serve as the primary technical point of contact for customers running large-scale training workloads. Onboard, troubleshoot, and optimize, often in real time.
  • Reliability & Performance Engineering: Define SLOs and error budgets that account for the unique failure modes of GPU infrastructure (ECC errors, NVLink degradation, NCCL timeouts). Own capacity planning across heterogeneous GPU fleets optimized for training throughput.
  • Networking & Fabric Health: Ensure the health and performance of high-speed interconnects (InfiniBand, RoCE, NVLink) that underpin distributed training. Diagnose and resolve fabric-level issues that degrade collective operations.
  • Observability: Build deep visibility into GPU utilization, memory pressure, interconnect throughput, training job performance, and hardware health. Go well beyond standard infrastructure metrics.
  • Automation & Tooling: Build production-grade automation for cluster provisioning, GPU health checks, job scheduling, self-healing, and firmware/driver lifecycle management.
  • Incident Leadership: Lead incident response for complex, multi-layer failures spanning hardware, networking, orchestration, and ML frameworks. Drive blameless postmortems and systemic fixes.

What We're Looking For
  • GPU Systems Expertise: Deep, hands-on experience operating large-scale GPU clusters (NVIDIA A100/H100/B200 or equivalent). You understand GPU memory hierarchies, ECC behavior, thermal throttling, and hardware failure modes from direct experience not documentation.
  • High-Performance Networking: Production experience with InfiniBand, RoCE, or NVLink fabrics in the context of distributed training. You can diagnose why an all-reduce is slow, identify a degraded link in a fat-tree topology, and reason about congestion control at scale.
  • Distributed Training & ML Frameworks: Working knowledge of how large training jobs actually run - NCCL, CUDA, PyTorch distributed, DeepSpeed, Megatron, FSDP, or similar. You don't need to write the models, but you need to understand what's happening at the systems level when a 1,000-GPU training run stalls.
  • Linux & Systems Internals: Expert-level Linux knowledge: kernel tuning, driver management (NVIDIA drivers, CUDA toolkit), cgroup/namespace internals, performance profiling at the syscall and hardware level.
  • Kubernetes & Orchestration: Strong experience running Kubernetes in production with GPU workloads, including device plugins, topology-aware scheduling, multi-cluster federation, and custom operators. Experience with Slurm or other HPC schedulers is equally valued.
  • Automation & Software Engineering: Strong engineering skills in Python, Go, or Bash. You build production-grade tools and services, not just scripts. Infrastructure-as-Code proficiency (Terraform, Helm, Ansible, or equivalent).
  • Observability & Monitoring: Hands-on experience building monitoring and alerting for GPU infrastructure, not just Prometheus/Grafana basics, but GPU-specific telemetry (DCGM, nvidia-smi, fabric manager metrics) integrated into actionable dashboards.
  • Incident Management: Proven track record leading incident response for complex distributed systems where the failure could be in hardware, firmware, networking, drivers, orchestration, or application code and you need to narrow it down fast.

Strong Candidates May Have
  • Distributed Storage: Experience with high-performance parallel file systems (VAST, Weka, Lustre, GPFS) and the checkpoint I/O and data-loading bottlenecks that come with large training runs.
  • Training Optimization: Experience profiling and optimizing distributed training performance: identifying stragglers, tuning collective communication strategies, improving MFU (Model FLOPs Utilization), and reducing idle GPU time across large runs.
  • Cluster Buildout & Hardware: Experience involved in physical cluster design - rack layout, power/cooling constraints, network topology design, and hardware validation/burn-in at scale.
  • Team Leadership: Experience leading or mentoring a team of infrastructure engineers. We're growing and need people who raise the bar for everyone around them.

Why You'll Love It Here
This is a high-impact, senior builder's role. You'll have significant ownership and autonomy to shape how our systems run at a foundational level, working directly with customers and providers while architecting the infrastructure backbone for reliable, scalable AI compute. You'll influence technical direction and help define what world-class AI infrastructure operations look like.
Andromeda Cluster is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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