Staff Engineer, GPU Front-End Infrastructure/ Methodology
Core
Shape and advance front-end implementation methodologies for high-quality, scalable RTL across complex GPU and SoC designs to enable design and verification teams.
Role type
Staff GPU Front-End Implementation Methodology Engineer
Builds
RTL flow and build system, agentic AI workflow, RTL CI/CD system, operational metrics collection, custom web applications, and open-source tool provisioning.
Domain
Semiconductor / High-performance computing / GPU architecture
Deliverable
production ML models | infrastructure
Required skills
Agentic AI tools and workflows design, Unix/Linux programming (Python, C++, Perl, Ruby, Go, shell scripting), Linux system debugging, DevOps practices, build automation, build systems (GNU Make), containerized environments, orchestration platforms (Docker, Kubernetes, OpenShift), RTL design concepts, testbench environments
Preferred skills
Familiarity with RTL design concepts and testbench environments
Technologies
Python, C++, Perl, Ruby, Go, shell scripting, GNU Make, Docker, Kubernetes, OpenShift
Responsibilities
Empower design and DV teams by removing friction from front-end workflows and addressing methodology gaps; Drive front-end RTL implementation methodologies ensuring scalability and adherence to performance/power objectives; Take ownership of moderate-to-complex projects to advance best practices and emerging technologies.
Seniority
Staff, hands-on IC with strategy & mentorship
