Compensation
$342K – $555K • Offers Equity
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About the Team
OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale.
About the Role
We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure.
In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads.
This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs.
Key Responsibilities
- Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs.
- Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware.
- Translate vendor specifications into expected real-world performance for AI workloads.
- Evaluate architectural aspects including:
- compute throughput and utilization
- memory systems (HBM, cache hierarchies, bandwidth constraints)
- data types and precision tradeoffs (FP16, BF16, FP8, etc.)
- interconnect and scaling behavior.
- Run benchmarks and profiling to validate hardware performance against workload requirements.
- Lead early bring-up and evaluation of engineering sample (ES) silicon.
- Partner with performance modeling and system architecture teams to align measured vs. modeled behavior.
- Provide actionable feedback to vendors to influence future silicon design and roadmap decisions.
Qualifications
- Have deep expertise in GPU or accelerator architecture, including performance and power tradeoffs.
- Understand AI workload behavior and how it interacts with hardware design choices.
- Are comfortable engaging directly with silicon vendors at a technical architecture level.
- Have hands-on experience with benchmarking, profiling, and performance analysis.
- Can translate low-level hardware details into system-level and workload-level impact.
- Are equally comfortable in theory (architecture) and practice (measurement/validation).
- Thrive in environments where you bridge internal teams and external partners.
Preferred Skills
- Experience working with or at companies like (e.g NVIDIA & AMD) or similar silicon providers.
- Familiarity with AI accelerator stacks, including GPUs, custom ASICs, or emerging architectures.
- Experience with early silicon bring-up or hardware validation workflows.
- Strong understanding of memory systems (HBM, DDR, cache hierarchies) and data movement bottlenecks.
- Experience with performance tooling, microbenchmarks, and workload characterization.
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