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.
Responsibilities
- 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.
Requirements
- 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 subsystems including CPU/GPU/NPU architectures, memory hierarchies, interconnects, and power management.
- Experience working with both internal engineering organizations and external strategic partners.
- Ability to lead cross-functional teams in fast-paced, execution-driven environments.
- Strong communication skills with the ability to influence technical direction across organizations.
Preferred Qualifications
- Experience with edge AI devices, embedded systems, or consumer hardware platforms.
- Background in performance modeling, silicon cost optimization, and workload-driven architecture.
- Familiarity with advanced process nodes and modern semiconductor development flows.