Machine Learning Solutions Engineer
As a Machine Learning Solutions Engineer at Lightning AI, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure. Lightning AI, founded in 2019 and known for PyTorch Lightning, offers an end-to-end platform for developing, training, and deploying AI systems. The company has merged with Voltage Park to provide developer-first software combined with cost-efficient, large-scale compute resources.
In this role, you will partner with customers to design and deploy comprehensive AI systems, encompassing model development and training, GPU infrastructure and cluster design, and distributed inference and production deployment. You will act as a technical architect, assisting customers in making critical decisions across compute, orchestration, and system design to meet their specific needs.
Key responsibilities include understanding customer ML workloads and infrastructure constraints, architecting end-to-end solutions across data pipelines and distributed training, and optimizing workloads across GPU clusters. You will also design and support deployments on Kubernetes, build and deliver technical demos and proofs of concept, and act as a bridge between customers, product, and engineering teams.
The ideal candidate will have 3–6+ years of experience in machine learning or AI engineering, solutions engineering, or ML consulting. A strong understanding of training versus inference workloads, model optimization techniques, and experience with GPU clusters and distributed systems is essential. Proficiency in Python, familiarity with Kubernetes, and excellent communication skills are also required.
The position is based in New York City, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. The annual base salary range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity. Benefits include comprehensive medical, dental, and vision coverage, retirement and financial wellness support, generous paid time off, paid parental leave, professional development support, wellness and work-from-home stipends, and a flexible work environment.