Deep Learning Solution Architect - RL and Post-training

Responsibilities

• Drive development, and optimization of Reinforcement Learning algorithms and infrastructure for Large Language Models and multimodal models.
• Develop and enable prompt open source models support in NVIDIA RL and post-training frameworks.
• Collaborate with internal research and engineering teams to adapt and validate state-of-the-art RL methods and optimizations to NVIDIA platform.
• Improve Reinforcement Learning initiatives and engagements with customers, providing technical guidance on integrating NVIDIA RL technologies into their AI workflows.
• Develop and maintain reusable toolchains, experiment management workflows, and technical documentation to accelerate both internal and customer-facing projects.
• What we need to see
• MS or PhD in Computer Science, Artificial Intelligence, Mathematics, or related fields, with solid foundations in algorithms and programming.
• 5+ years of experience (including research) in Reinforcement Learning, Large Language Model training, or multimodal learning.
• Proficient in PyTorch and familiar with RL training frameworks and workflows.
• Strong engineering skills with experience in distributed training, task orchestration, or evaluation pipelines.

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