Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Performance Optimization @ 3
Robotics
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The Robotics team focuses on unlocking general-purpose robotics and advancing AGI-level intelligence in dynamic, real-world settings. The team works across the model stack, integrating hardware and software across a broad range of robotic form factors.
The role focuses on improving model-serving efficiency for robotics research, optimizing inference performance and scalability, and contributing to the design of inference-friendly models.
Responsibilities
- Improve model serving, inference performance, and system efficiency.
- Drive kernel- and data-movement-level optimizations to improve system throughput and reliability.
- Partner with research and product teams to ensure models perform effectively at scale.
- Design, build, and improve critical serving infrastructure to support robotics growth and reliability needs.
- Help researchers develop inference-friendly models.
- Set technical direction and drive complex initiatives to completion.
Requirements
- Deep expertise in model performance optimization, particularly at the inference layer.
- Strong background in kernel-level systems, data movement, and low-level performance tuning.
- Interest in scaling high-performing AI systems serving real-world, multimodal workloads.
- Ability to navigate ambiguity and drive complex technical initiatives.
Benefits
- Equity, performance-related bonuses for eligible employees, and competitive benefits.
- Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for health, dependent care, and commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental, medical, and caregiver leave.
- Paid time off, company holidays, office closures, and paid sick or safe time.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily office meals and eligible meal delivery credits.
- Relocation support for eligible employees.
- Additional benefits may include charitable donation matching and wellness stipends.
The role is based in San Francisco, California, and follows a hybrid work model requiring three days in the office per week. OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities.
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