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Lightning AI is seeking a Senior Research Engineer to advance large language model training, fine-tuning, evaluation, and deployment across its platform and customer workloads. The role bridges cutting-edge research and production systems, focusing on improving model quality and training efficiency rather than building applications on top of existing models.
You will design and optimize training and post-training pipelines for transformer-based LLMs, improving model quality through supervised fine-tuning, continued pretraining, preference optimization, reinforcement learning, and evaluation. You'll build and enhance PyTorch-based training infrastructure, tooling, and developer workflows while optimizing distributed training across multi-GPU environments for throughput, memory efficiency, scalability, and GPU utilization.
The role requires deep experience training and improving transformer-based language models, strong software engineering fundamentals, and a passion for solving difficult problems across model training, evaluation, and AI systems. You'll investigate challenging model training issues including convergence, instability, communication overhead, and performance bottlenecks. Collaboration is key—you'll work closely with researchers, infrastructure engineers, and customers to translate research into reusable training and platform capabilities.
Lightning AI, founded in 2019, is the company behind PyTorch Lightning. Through its merger with Voltage Park, it combines developer-first software with cost-efficient, large-scale compute. The company serves solo researchers, startups, and large enterprises globally, with offices in New York City, San Francisco, Seattle, and London. It is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.
The role is hybrid with a minimum of 2 in-office days per week in San Francisco, Seattle, NYC, or London. Fully remote work is considered for candidates outside office hub locations. All employees participate in occasional team and company offsites.
