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 @ 6
Machine Learning
Python @ 6
Reinforcement Learning @ 6
- 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 Safety Oversight Research team advances capabilities for maintaining oversight over frontier AI models and ensuring deployed models are safe and beneficial. The work involves machine learning research in human-AI collaboration, reasoning, robustness, scalable oversight, and methods for identifying and mitigating AI misuse and misalignment.
Responsibilities
- Develop and refine AI monitor models to detect and mitigate known and emerging patterns of misuse and misalignment.
- Set research directions and strategies to make AI systems safer, more aligned, and more robust.
- Evaluate and design red-teaming pipelines to examine the end-to-end robustness of safety systems and identify areas for improvement.
- Conduct research to improve models' ability to reason about human values and apply these improvements to practical safety challenges.
- Coordinate and collaborate with cross-functional teams, including trust and safety, legal, policy, and research teams, to ensure products meet high safety standards.
Requirements
- Enthusiasm for AI safety and dedication to enhancing the safety of cutting-edge AI models for real-world use.
- 4+ years of experience in AI safety, particularly in areas such as reinforcement learning from human feedback (RLHF), human-AI collaboration, fairness, and bias.
- Ph.D. or another degree in computer science, machine learning, or a related field.
- Experience working with large-scale AI systems.
- 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
- 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 and dependent care expenses, as well as 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.
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