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Infra Engineer Jobs in California (NOW HIRING)

neww

Founding Platform Engineer

San Francisco, CA · On-site

Make the platform a product -- paved roads, golden paths, fast onboarding What you bring * 4+ years platform / SRE / infra engineering in production * Deep GCP fluency (or AWS at the equivalent level ...

Spiral

Software Engineer - Systems

San Francisco, CA · On-site

$203K - $241K/yr

Our users are AI/ML researchers and AI infra engineers developing models in complex domains, such as weather & climate, financial, time-series, genomics, point-clouds, videos, and images. They spend ...

Yutori

AI Engineer - LLM Infra

San Francisco, CA · On-site

$126K - $166K/yr

Scale infra for agentic inference (throughput and latency of perception-planning-action loops) * Build the foundations of a superhuman generalist web-agent * Work closely with product engineers to ...

Spiral

Software Engineer - Systems

San Francisco, CA

$203K - $241K/yr

Our users are AI/ML researchers and AI infra engineers developing models in complex domains, such as weather & climate, financial, time-series, genomics, point-clouds, videos, and images. They spend ...

Spiral

Software Engineer - Systems

San Francisco, CA · On-site

$200K - $275K/yr

Our users are AI/ML researchers and AI infra engineers developing models in complex domains, such as weather & climate, financial, time-series, genomics, point-clouds, videos, and images. They spend ...

Virio

Infrastructure Engineer

San Francisco, CA · On-site

$170K - $300K/yr

Infra Engineer Location: San Francisco (in-person, in-office, full-time ONLY) Compensation: $170K-$300K base + $25K-$50k cash bonus + top of market equity About Virio Virio is building the content ...

Virio

Infrastructure Engineer

San Francisco, CA · On-site

$170K - $300K/yr

Infra Engineer Location: San Francisco (in-person, in-office, full-time ONLY) Compensation: $170K-$300K base + $25K-$50k cash bonus + top of market equity About Virio Virio is building the content ...

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Showing results 41-60

All JobsInfra Engineer JobsInfra Engineer Jobs in California

Infra Engineer information

See California salary details

$45.9K

$125.4K

$179.6K

How much do infra engineer jobs pay per year?

As of Sep 12, 2026, the average yearly pay for infra engineer in California is $125,402.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $139,200.00 per year, depending on experience, location, and employer.

What is the difference between Infra Engineer vs Network Engineer?

AspectInfra EngineerNetwork Engineer
CertificationsCCNA, CompTIA Network+CCNA, CCNP, CompTIA Network+
Work EnvironmentData centers, cloud infrastructure, serversNetwork hardware, routers, switches, LAN/WAN
Industry UsageIT infrastructure, cloud providers, enterpriseTelecommunications, enterprise networks, ISPs

Infra Engineers focus on overall IT infrastructure, including servers and cloud systems, while Network Engineers specialize in designing and maintaining network hardware and connectivity. Both roles require similar certifications and often work in overlapping environments, but their core responsibilities differ in scope and focus.

How much do infrastructure engineers get paid?

Infrastructure engineers typically earn a median annual salary ranging from $70,000 to $120,000, depending on experience, location, and certifications. Senior roles or those with specialized skills in cloud platforms or network security may command higher salaries.

What do infrastructure engineers do?

Infrastructure engineers design, build, and maintain the hardware, networks, and systems that support an organization’s IT environment. They configure servers, manage cloud services, ensure system security, and troubleshoot technical issues to ensure reliable operation. Proficiency with tools like Linux, networking protocols, and scripting languages is often required.

What cities in California are hiring for Infra Engineer jobs?

Cities in California with the most Infra Engineer job openings:

Infra Engineer jobs near you
Infographic showing various Infra Engineer job openings in California as of August 2026, with employment types broken down into 87% Full Time, 8% Part Time, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $125,402 per year, or $60.3 per hour.

Member of Technical Staff (AI Infrastructure Engineer)

San Francisco, CA • On-site

Perplexity
Software Development • 11 - 50 employees
Learn more about Perplexityexternal

$220K - $405K/yr

Full-time

Re-posted 23 days ago

Key responsibilities

  • Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads

  • Manage and optimize Slurm-based HPC environments for distributed training of large language models

  • Develop APIs and orchestration systems for training pipelines and inference services

Job description

We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters
Responsibilities
  • Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads
  • Manage and optimize Slurm-based HPC environments for distributed training of large language models
  • Develop robust APIs and orchestration systems for both training pipelines and inference services
  • Implement resource scheduling and job management systems across heterogeneous compute environments
  • Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure
  • Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm
  • Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services
  • Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands
Qualifications
  • Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management
  • Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization
  • Experience with deploying and managing distributed training systems at scale
  • Deep understanding of container orchestration and distributed systems architecture
  • High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies)
  • Experience managing GPU clusters and optimizing compute resource utilization
Required Skills
  • Expert-level Kubernetes administration and YAML configuration management
  • Proficiency with Slurm job scheduling, resource management, and cluster configuration
  • Python and C++ programming with focus on systems and infrastructure automation
  • Hands-on experience with ML frameworks such as PyTorch in distributed training contexts
  • Strong understanding of networking, storage, and compute resource management for ML workloads
  • Experience developing APIs and managing distributed systems for both batch and real-time workloads
  • Solid debugging and monitoring skills with expertise in observability tools for containerized environments
Preferred Skills
  • Experience with Kubernetes operators and custom controllers for ML workloads
  • Advanced Slurm administration including multi-cluster federation and advanced scheduling policies
  • Familiarity with GPU cluster management and CUDA optimization
  • Experience with other ML frameworks like TensorFlow or distributed training libraries
  • Background in HPC environments, parallel computing, and high-performance networking
  • Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices
  • Experience with container registries, image optimization, and multi-stage builds for ML workloads
Required Experience
  • Demonstrated experience managing large-scale Kubernetes deployments in production environments
  • Proven track record with Slurm cluster administration and HPC workload management
  • Previous roles in SRE, DevOps, or Platform Engineering with focus on ML infrastructure
  • Experience supporting both long-running training jobs and high-availability inference services
  • Ideally, 3-5 years of relevant experience in ML systems deployment with specific focus on cluster orchestration and resource management

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