Deep Learning Solution Architect - RL and Post-training
NVIDIA· Architect, Solutions
Beijingon-sitePosted 1mo ago
About the role
NVIDIA AI computing-focused role in the Architect, Solutions team. Responsible for designing AI computing platform architectures, evaluating AI/HPC applications, and driving RL and post-training framework advancements for large language models and multimodal models.
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.
Qualifications
- 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.
- Ability to work independently with minimal day-to-day direction, and willingness to conduct exploratory experiments on frontier problems.
- Desire to be involved in multiple diverse and innovative projects.
- Outstanding verbal and written communication skills.
Skills
Required:Reinforcement LearningLarge Language Model trainingMultimodal learningPyTorchDistributed training
Nice to have:Experiment management
Last updated Sep 4, 2026. Interested? Apply on the company site.
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