SOC Architect

About the Team

OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform.

About the Role

We are seeking an experienced SoC Architect to lead the definition and development of next-generation custom AI silicon for edge deployments. This role will be responsible for shaping the architecture of highly efficient, high-performance SoCs optimized for machine learning inference and on-device intelligence.

You will work cross-functionally with internal engineering teams and external ecosystem partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery.

In this role you will:

• Define the architecture and technical roadmap for custom SoCs targeted for edge applications.

• Drive system-level tradeoff analysis across compute, memory, interconnect, power, thermal, and cost constraints.

• Architect energy-efficient ML compute subsystems optimized for inference workloads and real-world deployment environments.

• Collaborate with internal hardware, software, systems, and product teams to align architecture with platform needs.

• Partner with external silicon vendors, IP providers, and manufacturing partners to execute development plans.

• Lead hardware/software co-design efforts to maximize performance per watt and end-to-end system efficiency.

• Guide implementation teams through microarchitecture, RTL development, validation, and bring-up phases.

• Operate effectively in agile development environments and help teams deliver against aggressive schedules and milestones.

You might thrive in this role if:

• Proven experience defining and delivering complex SoC or ASIC architectures from concept to production.

• Deep understanding of AI/ML accelerators, edge inference workloads, and energy-efficient compute design.

• Strong knowledge of SoC