Machine Learning Solutions Engineer (ML + Infrastructure Focus)

<div class="content-intro"><h2><strong>Who We Are</strong></h2> <p>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.</p> <p>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.</p> <p>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.</p> <div class="c-message_actions__container c-message__actions">&nbsp;</div></div><h2><strong>What We're Looking For</strong></h2> <p>Lightning is looking for a <strong>Machine Learning Solutions Engineer</strong> with a focus on ML and Infrastructure to join ou Sales team in New York. As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure. You will partner with customers to design and deploy end-to-end AI systems, spanning:</p> <ul> <li>Model development and training</li> <li>GPU infrastructure and cluster design</li> <li>Distributed inference and production deployment</li> </ul> <p>This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.</p> <p><em>The role is hybrid out of one of our hub locations (New York City, San Francisco, Seattle) with an in-office requirement of at least 2 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time.</em></p> <p>&nb