NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.Today, we’re tapping into the unlimited potential of AI to define the...
This role involves leading technical partnerships with frontier AI labs to integrate NVIDIA's GPU and software stack into advanced AI workloads, from research to inference. The candidate will identify emerging technical requirements, optimize performance on NVIDIA platforms, and translate partner insights into product roadmap influence. It combines deep technical engagement with strategic collaboration across research, infrastructure, and product teams to drive joint innovation and scale AI systems.
Lead a team of data scientists focused on advancing AI-driven threat detection and agentic AI systems using large-scale cybersecurity data. Guide machine learning initiatives from research to production, collaborating with security and engineering teams to develop models for malware detection, behavioural analysis, and automated security responses. Drive innovation through research, technical mentorship, and strategic alignment in a high-impact, mission-driven environment.
Lead a team of data scientists focused on applying machine learning and large language models to cybersecurity challenges, including malware detection, behavioral threat analysis, and AI-driven security automation. Translate business needs into technical research objectives and guide the development of production ML systems at scale. Collaborate with security researchers, engineers, and product teams to solve complex, real-world adversarial problems using cutting-edge AI techniques.
This role involves building deep technical partnerships with leading AI research labs and model builders to integrate NVIDIA's GPU, systems, and software stack into cutting-edge AI workloads. The individual will identify performance bottlenecks, drive platform optimisation across training, post-training, and inference, and translate technical insights into product roadmap influence. It combines frontier AI research understanding with infrastructure expertise to shape both partner success and NVIDIA’s future platform development.
Develop and optimize compilers for AI inference workloads on next-generation NVIDIA GPUs, focusing on kernel generation, computational graph optimizations, and hardware-software co-design. Collaborate with cross-functional teams to advance AI performance and scale across datacenters. Work at the forefront of compiler innovation for deep learning and AI architectures.
This role involves developing advanced compiler technologies for AI inference and training workloads, focusing on kernel generation and computational graph optimizations for NVIDIA's GPUs. You'll solve complex compilation challenges, collaborate on hardware-software co-design, and help scale AI workloads across datacenters. The position emphasizes innovation in MLIR-based frameworks and optimizing performance on cutting-edge GPU architectures.
This role involves serving as a technical advisor and champion for the developer ecosystem in Healthcare and Lifesciences, accelerating workloads by integrating NVIDIA’s AI and computing platforms, and fostering co-innovation with partners. Responsibilities include technical enablement, ecosystem mapping, and cross-functional collaboration to drive adoption and solve real-world challenges.
Design and optimize GPU communication kernels for large-scale AI systems, focusing on low-level performance, memory efficiency, and integration with high-speed networking. Collaborate across hardware, software, and AI teams to co-develop GPU-aware communication primitives and programming models. Profile and tune end-to-end performance across compute, memory, and network boundaries to enable next-generation AI workloads.
Design and optimize GPU communication kernels for large-scale AI systems, focusing on collective and point-to-point operations. Work at the intersection of GPU architecture and networking, co-designing communication strategies with hardware and software teams. Develop low-level, GPU-resident primitives and tune performance across compute, memory, and network layers.
Design and optimize GPU communication kernels for large-scale AI systems, focusing on low-level GPU architecture and performance tuning. Collaborate with hardware and AI teams to co-develop communication strategies and programming models that align with GPU execution patterns. Profile and improve end-to-end performance of GPU-resident data movement across distributed accelerators.
Lead a team of data scientists focused on applying machine learning and large language models to cybersecurity challenges, including malware detection, behavioral analysis, and AI-driven threat response. Translate business needs into technical research objectives and guide the development of production ML systems at scale. Collaborate with security researchers and engineers to innovate in a high-impact, adversarial environment processing trillions of daily events.
Lead a team of data scientists focused on applying machine learning and large language models to cybersecurity challenges, including malware detection, behavioral threat analysis, and AI-driven security automation. Translate business needs into technical research objectives and collaborate across security, engineering, and product teams to deliver production ML systems at scale. Work on high-impact problems involving reverse engineering, decompilation, and adversarial dynamics within a platform processing trillions of daily events.
