关系基础模型工程师，现代数据栈
Relational Foundation Model Engineer, Modern Data Stack
我们的工作专注于视觉和AI计算的计算模型。二十年来，NVIDIA在视觉计算领域处于领先地位，这是计算机图形学的艺术与科学，我们发明了GPU。GPU也被证明在解决计算机科学中最复杂的问题方面非常有效。如今，NVIDIA的GPU模拟人类智能，运行深度学习算法，并作为能够感知和理解世界的计算机、机器人和自动驾驶汽车的“大脑”。我们希望与世界上最聪明的人一起壮大公司和团队，现在加入我们比以往任何时候都更加激动人心！
NVIDIA正在重新定义AI的可能性，而我们的关系基础模型团队正处于这一使命的最前沿。我们正在构建一个单一、统一的基础模型，能够理解任何关系数据库或异构图中的结构和关系——这是企业AI的一种根本性新方法。作为该团队的工程师，你不仅仅是在优化现有模型；你将设计并试验跨多种关系模式的新型Transformer和GNN架构。你的工作将直接影响涵盖推荐系统、需求预测、欺诈检测和预测性维护等实际应用——所有这些都由一个可扩展的模型驱动。你将与研究人员和工程师紧密合作，贯穿整个ML生命周期，从架构探索和大规模训练到训练后的优化和推理加速。这是一个难得的机会，可以参与可投入生产的基石研究，并塑造现代数据栈。如果你对图学习、关系推理以及构建远超单表基准的AI系统充满热情，那么这个团队就是你的选择。
你将从事的工作：
- 与研究人员/工程师合作，提升我们的基于Transformer和GNN的模型，使其能够在任何关系模式和异构图上无缝运行。
- 通过一个可扩展的基础模型，获得诸如预测、实体匹配、客户留存和欺诈检测等高影响力用例的实际操作经验。
- 运用你在机器学习和AI方面的知识解决实际挑战，同时为可扩展和适应性强的解决方案做出贡献，推动可能性的边界。
- 工作可能涉及现代ML系统的完整生命周期：从架构设计到大规模训练，再到训练后的优化和推理加速。
查看英文原文
Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join us!
NVIDIA is redefining what’s possible with AI, and our Relational Foundation Model team is at the forefront of that mission. We’re building a single, unified foundation model that understands the structure and relationships within any relational database or heterogeneous graph — a fundamentally new approach to enterprise AI. As an engineer on this team, you won’t just be fine-tuning existing models; you’ll be designing and experimenting with novel Transformer and GNN architectures that generalize across diverse relational schemas. Your work will directly impact real-world applications spanning recommendation systems, demand forecasting, fraud detection, and predictive maintenance — all powered by one extensible model. You’ll collaborate closely with researchers and engineers across the full ML lifecycle, from architecture exploration and large-scale training to post-training optimization and inference acceleration. This is a rare opportunity to contribute to foundational research that ships into production and shapes the modern data stack. If you’re excited about graph learning, relational reasoning, and building AI systems that go far beyond single-table benchmarks, this is the team for you.
What you’ll be doing:
- Collaborate with researchers/engineers to enhance our Transformer and GNN-based models to operate seamlessly over any relational schema and heterogeneous graph.
- Gain hands-on experience with high-impact use cases such as forecasting, entity matching, customer retention and fraud detection – all built on top of a single, extensible foundation model.
- Leverage your knowledge in ML and AI to tackle real challenges while contributing to scalable and adaptable solutions that push the boundaries of what’s possible.
- Work may span the full lifecycle of modern ML systems: from architecture design/training to post-training optimization and inference acceleration.
- You will contribute to our next generation of the Relational Foundation Model.
What we need to see:
- MS or PhD in Machine Learning, Computer Science, or equivalent program
- Proficiency in Python and deep learning frameworks, such as PyTorch
- At least 8 years of research experience in designing ML algorithm solutions
- Practical experience in using Predictive Models in Real World Applications
Ways to stand out from the crowd:
· Familiarity with graph-based machine learning; publications at venues such as NeurIPS, ICLR, ICML, or similar
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
Originally posted on Himalayas