Why This Job is Featured on The SaaS Jobs
This role stands out in the SaaS ecosystem because it sits at the infrastructure layer that increasingly underpins modern AI-enabled software products. OpenAI’s focus on AI-native silicon and hardware software co-design reflects a trend where software outcomes depend on tight integration across the stack, from model behavior to compute, memory, and interconnect choices. For SaaS professionals tracking where platform differentiation is heading, this is a window into how foundational capabilities get built rather than simply consumed via cloud services.
Over time, work like this compounds into rare, transferable leverage in SaaS-adjacent environments: performance modeling tied to real workloads, cross-functional iteration with compilers and ML systems, and an understanding of how production constraints shape product capabilities. Experience translating abstract workload needs into concrete architecture and RTL decisions is also relevant to platform teams that need to reason about cost, latency, and reliability at scale.
The role is best suited to early-career engineers who prefer hands-on ownership and are comfortable collaborating across disciplines with different success metrics. It will appeal to those who enjoy moving between theory and implementation, and who want their technical scope to extend beyond a single codebase into the systems that ultimately determine what software can deliver.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.
About the Role
We’re looking for a RTL Engineer to design and implement key compute, memory, and interconnect components for our custom AI accelerator. You’ll work closely with architecture, verification, physical design, and ML engineers to translate AI workloads into efficient hardware structures. This is a hands-on design role with significant ownership across definition, modeling, and implementation.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
Responsibilities
Produce clean, production-quality microarchitecture and RTL for major accelerator subsystems
Contribute to architectural studies including performance modeling and feasibility analysis.
Collaborate with software, simulator, and compiler teams to ensure hardware/software co-design and workload fit.
Partner with DV and PD to ensure functional correctness, timing closure, area/power targets, and clean integration.
Build and review performance and functional models to validate design intent.
Participate in design reviews, documentation, and bring-up support across the full silicon lifecycle.
You Might Thrive In This Role If You Have:
Graduate-level research or industry experience in computer architecture, AI/ML hardware–software co-design, including workload analysis, dataflow mapping, or accelerator algorithm optimization.
Expertise writing production-quality RTL in Verilog/SystemVerilog, with a track record of delivering complex blocks to tape-out.
Experience developing hardware design models or architectural simulators, ideally for AI/ML or high-performance compute systems.
Familiarity with industry-standard design tools (lint, CDC/RDC, synthesis, STA) and methodologies.
Ability to work cross-functionally with architecture, ML systems, compilers, and verification teams.
Strong problem-solving skills and ability to think across abstraction layers, from algorithms to circuits.
Passion for building industry-leading massive-scale hardware systems.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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