# Research Engineer - CUDA Kernel Engineering - Company: [Voltai Careers]() - Location: Palo Alto Office - Team: Engineering - Employment type: Full Time - Posted: November 6, 2025 ## Job description **About Voltai** Voltai is developing world models, and agents to learn, evaluate, plan, experiment, and interact with the physical world. We are starting out with understanding and building hardware; electronics systems and semiconductors where AI can design and create beyond human cognitive limits. **About the Team** Backed by Silicon Valley’s top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents. **About the Role** You will develop, integrate, and optimize **state-of-the-art CUDA kernels** to power AI models that accelerate semiconductor design and verification. Your work will enable large-scale model training, inference, and reinforcement learning systems that reason about circuit layouts, generate and validate RTL, and optimize chip architectures — running efficiently across thousands of GPUs. You’ll build tools, performance benchmarks, and integration layers that push the limits of GPU utilization for compute-intensive workloads in AI-driven hardware design. Working closely with researchers and engineers, you’ll help make Voltai the world’s leading AI + semiconductor research organization. You’ll also release your kernels and tooling as contributions to the **open-source AI and HPC** [**ecosystems**.](http://ecosystems.You) **You might thrive in this role if you have experience with** * **Writing and optimizing CUDA kernels** for large-scale AI workloads (attention, routing, graph-based operations, physics-inspired operators, etc.) * **Profiling and optimizing GPU performance** for custom compute or memory-bound workloads * **Integrating custom kernels** into cutting-edge training and inference frameworks (e.g., PyTorch, Megatron, vLLM, TorchTitan) * Working with **the latest NVIDIA hardware and software stacks** (Hopper, Blackwell, NVLink, NCCL, Triton) * **Building GPU-accelerated primitives** for graph reasoning, symbolic computation, or hardware simulation tasks * Collaborating with **AI researchers and semiconductor experts** to translate domain-specific workloads into high-performance GPU code ## Apply [Apply on Voltai Careers]() Canonical job page: