Deep Learning Solution Architect - RL and Post-training

Job description

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers. You will work closely with industry sales, developer relationship managers and product teams in the hiring position. What you’ll be doing: 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. 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. Ways to stand out from the crowd: Experience with RLHF, GRPO, DPO, or other alignment and post-training methods for LLMs. Experience with scale-out HPC or cloud architectures for large-scale model training. CUDA optimization or GPU performance tuning experience. Experience with agentic AI systems, code generation models, or multimodal RL. Publications in top-tier venues in RL, NLP, or multimodal learning. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.