d-Matrix

Own end-to-end performance for d-Matrix’s inference cloud, diagnosing latency, throughput, and stability issues across orchestration, serving, operating-system, networking, and accelerator layers. This senior technical role uses profiling, benchmarking, and systems expertise to make heterogeneous AI workloads perform as well as bare metal.

Own the end-to-end testing infrastructure and release strategy for d-Matrix’s Inference Cloud, spanning Kubernetes deployments, shared accelerator hardware, and customer-facing inference services. This staff-level role will build reliable automation, define release gates, and enable predictable rollbacks and independent component releases.

Lead the design and hands-on development of AI-enabled test and software-delivery automation for advanced AI inference hardware. This principal role will establish shared agent infrastructure, evaluation methods, and quality-engineering workflows used across the organization.

Senior Infrastructure Engineer responsible for operating and improving the Kubernetes, CI, Linux, and compute environments that support d-Matrix engineering and AI inference demonstrations. The role combines incident response, automation, observability, upgrades, and on-call ownership in a remote U.S. environment.

Lead d-Matrix’s Bazel build-out, completing the migration and designing distributed build infrastructure for MLIR, Rust, C++, and Python codebases. You will improve build reliability and speed across developer machines, CI, and hardware-attached runners.

Build reliable developer automation and release infrastructure that diagnoses CI/CD failures, identifies problematic merges, and reduces engineering toil across cloud and on-prem environments. This Staff-level role combines deterministic software automation with selective AI techniques to improve developer time-to-signal.

Lead reliability and automation for d-Matrix’s AI infrastructure across colocation facilities, on-premises GPU clusters, cloud environments, and customer-facing platforms. This hands-on role owns infrastructure end to end, from bare-metal provisioning and Kubernetes operations through incident response and observability.

Own the runtime, low-level drivers, and systems software that make d-Matrix’s in-memory AI inference silicon perform. This staff-level role combines embedded software architecture, runtime performance ownership, and distributed inference infrastructure development in a hybrid Santa Clara setting.