Design and build full-stack applications that integrate AI-driven physics simulation models into real-world engineering workflows. Collaborate directly with customers and technical teams to prototype, deploy, and iterate on high-impact tools across aerospace, energy, and advanced manufacturing. Work across backend services, APIs, and cloud infrastructure while contributing to core platform development.
Lead high-impact research initiatives to develop AI-driven simulation models for engineering and physical systems, translating complex physics problems into mathematical and machine learning formulations. Collaborate with cross-functional teams to integrate research into production, publish findings, and mentor junior researchers. The role emphasizes innovation in deep learning for PDEs, geometric data, and generative modeling with real-world industrial applications.
Lead the development and scaling of Gaia, Wayve’s video world model that predicts future driving scenarios from past context. Drive large-scale training of foundation models, improve synthetic scenario generation, and collaborate with research and engineering teams to enhance autonomous driving systems. Focus on model architecture, training strategy, and end-to-end delivery in a high-impact, fast-paced environment.
Build and operate cloud-based software products for internal and external users, focusing on services, APIs, integrations, and web interfaces within a high-ownership, end-to-end team. Work across microservices, frontends, and cloud infrastructure to improve reliability and customer experience while supporting production systems and partner integrations.
Design and optimize deep learning models for high-performance inference on GPU platforms, focusing on production deployment and performance tuning of Cosmos World Foundation Models. Collaborate with research and engineering teams to profile and accelerate workloads across diverse hardware. Work at the intersection of AI, systems, and GPU optimization to enable physical AI applications in robotics, autonomous vehicles, and simulation.
This role involves optimizing and deploying large-scale deep learning models for high-performance inference on GPU platforms, specifically within NVIDIA's Cosmos World Foundation Models platform. The engineer will work at the intersection of deep learning and systems optimization, profiling workloads, removing bottlenecks, and ensuring efficient deployment across diverse hardware. The position requires strong expertise in PyTorch, inference optimization frameworks, and GPU performance tuning.
This role involves leading the deployment of cutting-edge AI models into production environments by embedding directly with customer teams. The engineer will scope, build, and deliver full-stack solutions, translating complex problems into working systems while gathering real-world feedback to influence product development. Success requires rapid iteration, technical ownership, and clear communication across internal and external stakeholders.
Design and build systems to proactively detect and enforce against abuse on OpenAI's products, including monitoring for new and existing features. Investigate critical escalations involving sensitive content and collaborate with product, policy, and engineering teams to develop scalable safety solutions. Develop detection prototypes and improve automation using data science and machine learning techniques.
This role involves collaborating with top game developers to optimize GPU performance and advance rendering technologies, with a focus on path tracing and neural graphics. The engineer will develop and tune AI models, work closely with NVIDIA's architecture and driver teams, and contribute to next-generation GPU innovations. Activities include building technical demos, profiling algorithms, and presenting research at conferences.
This role involves collaborating with top AAA game developers to optimize GPU performance and advance rendering technologies, particularly in path tracing and neural graphics. The engineer will develop and tune AI models, work closely with NVIDIA's architecture and driver teams, and contribute to next-generation GPU innovations. Responsibilities include creating technical demos, publishing research, and presenting at conferences.
This role involves collaborating with top game developers to optimize GPU performance and advance rendering technologies such as path tracing and neural graphics. The engineer will develop and optimize AI models and rendering algorithms, work closely with NVIDIA's architecture and driver teams, and create technical demonstrations and whitepapers. The position emphasizes innovation in AI-driven graphics and requires deep expertise in real-time rendering, GPU programming, and system-level optimization.
This role involves developing and automating test frameworks for a distributed system that manages thousands of resources across NVIDIA teams. The engineer will create test plans, automate validation for UIs, APIs, and performance, and integrate testing into CI/CD pipelines. A key focus is leveraging AI and LLMs—such as prompt engineering and fine-tuning—to enhance test automation, generate test cases, and improve QA efficiency across complex cloud and Kubernetes-based environments.
This role involves designing and delivering end-to-end networking solutions that integrate NVIDIA GPUs and networking technologies for cloud, AI, HPC, and enterprise customers. The architect will define reference architectures, lead technical pre-sales engagements, respond to RFPs, conduct product demonstrations, and provide technical leadership during complex deployments. Close collaboration with sales, engineering, and product marketing teams ensures customer requirements inform product development and strategy.
Design and implement end-to-end data center networking solutions integrating NVIDIA GPUs and networking technologies for cloud, HPC, telco, and enterprise clients. Lead technical pre-sales engagements, develop custom proofs-of-concept, and support complex deployments while providing feedback to engineering teams on product improvements. Focus on AI factories, LLMs, and high-performance networking architectures.
This role involves working closely with government clients and partners to design and deploy AI-driven solutions using NVIDIA's hardware and software technologies. The Solution Architect will develop technical collateral, lead proof-of-concept initiatives, and guide field teams in implementing AI workflows across public sector challenges. A strong focus is placed on computer vision, generative AI, and MLOps, with an emphasis on translating mission goals into scalable technical strategies.
