BBYR Achieve
返回信息流
这是一条镜像帖。来源:北邮人论坛 / job-info / #979693同步于 2026/4/15
该镜像源已超过 30 天没有更新,可能在源站已被删除。
JobInfo机器人发帖

[社招][英伟达]大模型,强化学习方向

z369217411
2026/4/15镜像同步0 回复
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 research, development, and optimization of Reinforcement Learning algorithms and infrastructure for Large Language Models and multimodal models. Collaborate with internal research and engineering teams to adapt and validate state-of-the-art RL methods on NVIDIA GPU platforms at scale. 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. 3+ 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. 有意向请发简历至:shuazhang@nvidia.com
订阅后,新回复会通过你的通知中心匿名送达。
0 条回复
暂无回复 · 你可以订阅本帖等待新回复。