Infrastructure Engineer (GPU & Compute)

Posted 2 Days Ago
4 Locations
Remote or Hybrid
180K-220K Annually
Senior level
Artificial Intelligence • Machine Learning • Software
Lightning empowers everyone to build AI.
The Role
Build, validate, and operate large-scale bare-metal GPU infrastructure for AI/ML and HPC workloads. Responsibilities include managing Linux systems, image pipelines, test clusters, provisioning, firmware and driver validation, GPU diagnostics, performance analysis with NVIDIA DCGM, automation, virtualization, and hardware management interfaces. The role requires troubleshooting across hardware and software layers while collaborating with infrastructure, hardware, data center, platform, and ML teams.
Summary Generated by Built In
Who We Are

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 Way We Work

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.
 
What We're Looking For

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will help bring up, validate, and operate 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—owning system diagnostics and validation, developing automation, improving reliability, and ensuring clusters are ready to support demanding AI/ML and HPC workloads.

You will play a key role in GPU and system-level qualification, running validation environments and test clusters, and improving the tooling and workflows that support infrastructure bring-up at scale. This includes owning and evolving our image pipeline alongside provisioning and validation systems to ensure our infrastructure is consistent, performant, and reliable from day one.

This role may be fully remote within the U.S., or hybrid out of one of our office hubs (NYC, SF, Seattle, or London), with occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll DoSystems Bring-Up & Validation
  • 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 NeedRequired 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.

Benefits may vary by location, team, and role.


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.

Skills Required

  • 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 or programming languages for automation
  • Ability to debug complex issues across hardware, operating systems, GPUs, and system software
  • Experience with high-performance interconnects such as InfiniBand or 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
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The Company
HQ: New York, NY
50 Employees
Year Founded: 2019

What We Do

Our platform provides intuitive open source tools, powerful cloud infrastructure and expertise to help you build AI securely.

Why Work With Us

Our team has shaped groundbreaking AI projects like PyTorch and PyTorch Lightning. We’re educators, innovators, and collaborators, united by a mission to democratize AI. A hybrid based company headquartered in New York City, we value in-person time for collaboration while still allowing flexibility.

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