12 months ago
Palo Alto, CA, USASenior
Responsibilities
- Develop, integrate, and optimize CUDA kernels for large-scale AI training, inference, and reinforcement learning workloads.
- Profile and optimize GPU performance for custom compute-bound and memory-bound workloads.
- Integrate custom kernels into training and inference frameworks such as PyTorch, Megatron, vLLM, and TorchTitan.
- Build performance tools, benchmarks, integration layers, and GPU-accelerated primitives for graph reasoning, symbolic computation, and hardware simulation.
- Collaborate with AI researchers and semiconductor experts to translate domain-specific workloads into high-performance GPU code.
- Release kernels and tooling as contributions to open-source AI and HPC ecosystems.
Requirements
- Experience writing and optimizing CUDA kernels for large-scale AI workloads, including attention, routing, graph-based operations, or physics-inspired operators.
- Experience profiling and optimizing GPU performance.
- Experience integrating custom kernels with AI training and inference frameworks.
- Experience with NVIDIA hardware and software stacks, including Hopper, Blackwell, NVLink, NCCL, and Triton.
- Experience building GPU-accelerated primitives for graph reasoning, symbolic computation, or hardware simulation.
- Ability to collaborate with AI researchers and semiconductor experts on domain-specific performance engineering.
Tech Stack
Categories
About Voltai
Volt AI builds a real-time video intelligence platform for physical security teams, unifying existing cameras and systems to track people and objects across sites and streamline incident response via an intuitive 3D map and case tools. It sells enterprise software that runs with edge AI and integrates into security workflows. Founded in 2019 and headquartered in Washington, DC, the company is privately held.