Infrastructure Engineer (GPU & Compute)

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 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 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 & Op…