Infrastructure Engineer (GPU & Compute)

Infrastructure Engineer (GPU & Compute)

Full-Time Home office (partial)
Lightning AI

At a Glance

  • Tasks: Own and evolve GPU infrastructure, manage image pipelines, and improve system performance.
  • Company: Join Lightning AI, the creators of PyTorch Lightning, in a fast-paced tech environment.
  • Benefits: Enjoy competitive salary, equity options, unlimited PTO, and wellness stipends.
  • Other info: Flexible work model with opportunities for professional growth and development.
  • Why this job: Make a real impact on AI systems while working with cutting-edge technology.
  • Qualifications: 5+ years in infrastructure engineering, strong Linux and GPU experience required.

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here’s what that looks like in practice:

  • Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping.
  • Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through.
  • Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together.
  • Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work.
  • Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most.
  • Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact.

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team. In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software—developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads.

You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

  • Systems, Image & Validation Infrastructure: Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure. Run and maintain test clusters used for system validation, diagnostics, and bring-up. Validate firmware, drivers, and OS images across compute and GPU-enabled systems. Support hardware qualification efforts for next-generation platforms.
  • GPU Diagnostics & Performance: Own GPU diagnostics and validation workflows across large-scale infrastructure. Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers. Analyze system and GPU performance using tools such as NVIDIA DCGM. Identify failure patterns and drive improvements in system stability and validation coverage.
  • Automation & Tooling: Build and maintain automation for provisioning, validation, and system bring-up. Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead. Improve the reliability, repeatability, and scalability of image pipelines and validation systems.
  • Systems & Operations: Manage and operate Linux-based systems in production and validation environments. Manage virtualization technology. Support bare-metal provisioning workflows, including PXE and image-based systems. Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging.
  • Cross-Functional Collaboration: Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation. Collaborate with platform and ML teams to ensure systems meet workload requirements. Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure.

What You’ll Need

  • Required Qualifications: 5+ years of experience in infrastructure engineering, systems engineering, or related roles. Strong Linux systems experience in production environments. Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM. Familiarity with bare-metal provisioning and system bring-up workflows. Proficiency in Python or similar scripting/programming languages for automation. Ability to debug complex issues across hardware, OS, GPUs, and system software.
  • Ideal Experience: Experience with high-performance interconnects (e.g., InfiniBand, NVLink). Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows. Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish. Data center operations experience, including working with physical hardware. Experience supporting AI/ML or HPC workloads at scale. Experience with GPU validation frameworks or large-scale hardware qualification processes.

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $180,000 — $220,000 USD.

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success:

  • Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents.
  • Meaningful Equity: RSUs that give employees a stake in the company's long-term success.
  • Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.).
  • Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance.
  • Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge.
  • Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments.
  • Professional Development: Annual learning and development allowance to support your professional growth.
  • Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being.
  • Sabbatical Program: Four weeks of paid sabbatical leave after four years of service.
  • Flexible Work: Flexible schedules and a hybrid work model for our office-based teams.
  • In-Office Meals: Complimentary meals at our office hubs.

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Infrastructure Engineer (GPU & Compute) employer: Lightning AI

Lightning AI is an exceptional employer that fosters a collaborative and inclusive work culture, where innovation thrives and employees are empowered to take ownership of their projects. With offices in vibrant cities like London, our team enjoys a flexible work environment, comprehensive benefits, and ample opportunities for professional growth, making it an ideal place for passionate Backend Engineers to advance their careers while contributing to cutting-edge AI technology.

Lightning AI

Contact Details:

Lightning AI Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Infrastructure Engineer (GPU & Compute)

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Lightning AI or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Lightning AI.

Tap into Online Developer Communities

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Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Lightning AI that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Infrastructure Engineer (GPU & Compute)

Linux Systems Management
GPU Diagnostics
Image Management
Automation with Python
System Validation
Bare-Metal Provisioning
Hardware Qualification

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Lightning AI.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Lightning AI and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Lightning AI

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Lightning AI uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.