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HPC AI Linux Systems Administrator
This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.Who We Are:
Hewlett Packard Enterprise is the global edge\-to\-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
This position will support government accounts. Therefore, due to federal export\-control regulations, the selected candidate must hold U.S. citizenship, U.S. lawful permanent resident/Green Card status or otherwise have a category of refugee/asylee status enabling them to perform the role without requiring a license under the International Traffic in Arms Regulations (ITAR) or Export Administration Regulations (EAR).
The Data Center Administration team is seeking a Senior Linux System Administrator to provide advanced system administration and lab operations support for hardware, network, and software environments used by HPE HPC \& AI Performance Engineering teams. These environments support internal product development, performance engineering, ISV validation, and customer\-facing sales and benchmarking activities.
This role serves as a senior technical contributor and lab expert, providing design guidance, operational leadership, and escalation\-level troubleshooting across complex HPC and AI lab environments. The position partners closely with engineering teams, infrastructure support groups, and external partners to ensure lab stability, availability, and effective use of resources.
The Senior Linux System Administrator contributes to continuous improvement of lab processes, policies, and standards, prioritizes lab requests, mentors junior staff, and supports future lab expansion and facility transitions.
Essential Job Functions and Duties
- Image, configure, and upgrade servers with Linux operating systems, including firmware updates and switch configuration to support lab environments.
- Configure and manage multiple root slots hosting varied operating system images in support of HPC cluster provisioning, validation, and testing workflows.
- Provide design guidance and operational support for virtualized lab infrastructure, including virtual server administration and the design of highly available, fault\-tolerant environments.
- Provide design guidance for lab storage solutions, including installation, configuration, and performance management of high\-performance storage systems (e.g., Lustre) to support sales, benchmarking, and partner activities.
- Provide guidance for hardware and software installation and configuration, including advanced hardware diagnostics and coordination with infrastructure support teams to resolve power, CPU, and GPU issues.
- Collaborate with AI benchmarking, R\&D, and performance engineering teams to design and operate lab environments that meet internal, partner, and customer requirements.
- Design lab layouts, networks, and operational policies that meet functional needs while adhering to cybersecurity and asset protection standards.
- Prioritize and coordinate lab work activities to ensure timely delivery of high\-impact requests and effective utilization of lab resources.
- Make recommendations on lab resource usage, capacity planning, and future expansion to support evolving business and engineering needs.
- Oversee and support lab transitions, including facility moves and infrastructure refresh activities.
- Install, configure, and support job scheduling and resource management tools to maximize lab utilization.
- Serve as a technical mentor to junior system administrators and lab staff, providing guidance on best practices, troubleshooting, and operational standards.
- Communicate lab successes, risks, failures, and issues to management in a timely and professional manner.
- Work effectively with remote administrators, vendors, and partners when specialized expertise or additional support is required.
Job\-Specific Competencies
- Communication – Communicates clearly and effectively in both written and verbal forms; collaborates well with diverse technical teams.
- Creativity / Innovation – Applies creative problem\-solving approaches and contributes to continuous improvement of lab processes and capabilities.
- Customer Service – Demonstrates a service\-oriented mindset when supporting internal teams, partners, and stakeholders.
- Job Knowledge – Maintains deep technical knowledge of Linux systems, lab operations, and HPC/AI infrastructure.
- Problem Solving / Analysis – Breaks down complex technical issues, identifies root causes, and develops effective solutions.
- Quality – Demonstrates attention to detail, accuracy, and reliability.
- Technical Skills – Strong expertise in Linux system administration with working knowledge of networking, storage, virtualization, and hardware platforms.
Education and Experience
- Bachelor’s degree in Computer Science, MIS, or a related technical field required mainly System Administration.
- Minimum of 5\-7 years of Linux system administration experience required, preferably in HPC, AI, or lab\-based environments.
- Candidates with strong Linux or network administration backgrounds and demonstrated interest in advanced lab system administration will also be considered.
- This role works as part of a team of system administrators and lab staff and reports to the Data Center Administration Manager.
What We Can Offer You:
Health \& Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal \& Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.
Let's Stay Connected:
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
\#unitedstatesJob:
Engineering ServicesJob Level:
Specialist
"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
– United States of America: Annual Salary USD 98,000 \- 185,200 in Colorado // 105,500 \- 213,500 in California // 92,600 \- 213,500 in Minnesota \& Texas \& Wisconsin
The listed salary range reflects base salary. Variable incentives may also be offered."
Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new\-hire\-enrollment.html
The estimated job application period closure is September 28 2026; this timeline is provided for transparency and internal planning purposes.
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.
Recruitment Fraud Alert
We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat\-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.
All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.
Salary Context
This $98K-$185K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Hewlett Packard Enterprise | HPE, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($141K) sits 22% below the category median. Disclosed range: $98K to $185K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Hewlett Packard Enterprise | HPE AI Hiring
Hewlett Packard Enterprise | HPE has 4 open AI roles right now. They're hiring across AI Engineering Manager, AI/ML Engineer, AI Product Manager. Positions span Cupertino, CA, US, San Jose, CA, US, Spring, TX, US. Compensation range: $185K - $412K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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