Member of Technical Staff

Lucid Computing•San Francisco, CA

About The Position

Lucid builds verifiable compute infrastructure: systems that produce cryptographic evidence about what AI hardware is doing, where it's doing it, and whether the computation matched what was claimed. We are hiring in several areas including applied cryptography, hardware and silicon security, GPU/compilers/ML systems, distributed systems and infrastructure, networking and measurement, and trusted environments and security engineering. If your specialty is adjacent to these but not on the list, apply anyway and tell us where you'd fit.

Requirements

Real depth in your area of expertise, or unusual velocity that substitutes for years of experience.
Strong systems programming skills in Rust, C, C++, or Go.
Ability to operate with a high correctness bar suitable for security-critical infrastructure.
Demonstrated ownership: ability to take a problem from an ambiguous question to a shipped system without constant supervision.
Experience explaining systems to customers, vendors, and regulators.

Nice To Haves

Experience building cryptographic systems that have shipped.
Ability to reason about threat models fluently.
Knowledge of GPU architecture and mapping logical tensors to physical hardware.
Experience building distributed systems where correctness and availability are critical.
Comfort with noisy physical-world signals and adversaries.
Prior work in classified, regulated, or high-assurance settings.
Formal methods or verification tooling experience.
Open-source contributions to infrastructure or security projects.
Experience at a company at a similar stage (sub-50 people, pre-Series A or Series A).
Genuine interest in AI safety, governance, or responsible deployment.

Responsibilities

Build verifiable compute infrastructure that produces cryptographic evidence about AI hardware operations.
Develop applied cryptography solutions including attestation protocols, proof systems, and evidence formats.
Work on hardware and silicon security, including roots of trust, TEEs, secure enclaves, and attestation on modern accelerators.
Engage in direct technical work with silicon vendors.
Perform static analysis of GPU kernels to extract memory access patterns and computational structure.
Derive workload behavior from their definitions using tools like CUDA, Triton, CUTLASS, PTX/SASS, MLIR/LLVM.
Build the platform for collecting, storing, and serving verification evidence at cluster scale.
Develop the control plane for distributed systems.
Implement networking solutions involving network taps, timing and latency measurement, and geolocating compute.
Build and defend hardened compute environments, considering physical and supply-chain security.