Description
Compensation
$380K – $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
The Foundations team focuses on how model behavior changes as we scale models, data, and compute. The team studies the interactions between model architecture, optimization, and training data, and uses those insights to guide how new models are designed and trained.
About the Role
In this role, you will build the systems that enable advanced AI models to run efficiently at scale. You will operate at the intersection of model research and systems engineering, translating new architectural ideas into high-performance inference systems that surface real tradeoffs in performance, memory, and scalability.
Your work will directly influence how models are designed, evaluated, and iterated on across the research organization. By developing and evolving high-performance inference infrastructure, you will enable researchers to explore new ideas with a clear understanding of their computational and systems implications.
This is not a product-serving role. Instead, it is a research-enabling systems role focused on performance, correctness, and realism - ensuring that AI research is grounded in what can actually scale.
In this role, you will:
- Design and build high-performance inference runtimes for large-scale AI models, with a focus on efficiency, reliability, and scalability.
- Own and optimize core execution paths, including model execution, memory management, batching, and scheduling.
- Develop and improve distributed inference across multiple GPUs, including parallelism strategies, communication patterns, and runtime coordination.
- Implement and optimize inference-critical operators and kernels informed by real-world workloads.
- Partner closely with research teams to ensure new model architectures are supported accurately and efficiently in inference systems.
- Diagnose and resolve performance bottlenecks through profiling, benchmarking, and low-level debugging.
- Contribute to observability, correctness, and reliability of large-scale AI systems.
You might thrive in this role if you:
- Have experience building production inference systems, not just training or running models.
- Are comfortable with GPU-centric performance engineering, including memory behavior and latency/throughput tradeoffs.
- Have worked on multi-GPU or distributed systems involving batching, scheduling, or runtime coordination.
- Can reason end-to-end about inference pipelines, from request handling through execution and output streaming.
- Are able to understand research ideas and implement them within real system and performance constraints.
- Enjoy solving hard, ambiguous systems problems that only emerge at scale.
- Prefer hands-on technical ownership and execution over abstract design work.
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.
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.
Required Skills
- Experience building production inference systems, not just training or running models
- Comfortable with GPU-centric performance engineering, including memory behavior and latency/throughput tradeoffs
- Multi-GPU or distributed systems involving batching, scheduling, or runtime coordination
- Reasoning end-to-end about inference pipelines, from request handling through execution and output streaming
- Understanding research ideas and implementing them within real system and performance constraints
- Solving hard, ambiguous systems problems that only emerge at scale
- Hands-on technical ownership and execution over abstract design work
Preferred Skills
- Experience working with large-scale AI models
- Distributed inference across multiple GPUs
- Parallelism strategies, communication patterns, and runtime coordination
- Implementing and optimizing inference-critical operators and kernels
- Observability, correctness, and reliability of large-scale AI systems
- 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