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
Machine Learning
Python @ 5
- 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
Models are becoming increasingly capable, moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. The Preparedness team works to mitigate frontier risks and support the safe deployment of advanced AI systems through measurement, mitigation, and coordination.
Responsibilities
- Identify emerging AI safety risks and develop methodologies for exploring and mitigating their impact.
- Build and continuously refine evaluations to assess the extent of AI safety risks, working with internal or external domain experts where appropriate.
- Set research directions and strategies to make AI systems safer, more aligned, and more robust.
- Contribute to best-practice guidelines for AI safety at OpenAI and across the industry.
- Evaluate and design red-teaming pipelines to examine the end-to-end robustness of safety systems and identify areas for improvement.
- Develop novel safety mitigations and apply techniques from interpretability, control, and alignment to help ensure the safety of deployed models.
- Collaborate cross-functionally with experts in areas such as misalignment, cybersecurity, and biology to develop an effective end-to-end safety stack.
Requirements
- Enthusiasm for long-term AI safety and thoughtful consideration of technical paths to safe AGI.
- Willingness to apply methods from interpretability, robustness, alignment, and control to improve model safety.
- At least 2 years of experience in AI safety, particularly in areas such as RLHF, human-AI collaboration, interpretability, or control.
- Ph.D. or another degree in computer science, machine learning, or a related field.
- Experience working with large-scale AI systems.
- At least 4 years of research engineering experience.
- Proficiency in Python or similar programming languages.
- Alignment with OpenAI's mission of building safe, universally beneficial AGI.
Benefits
- Base salary of $295,000–$445,000 per year.
- Equity, performance-related bonuses for eligible employees, and comprehensive 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.
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