Researcher, Robustness & Safety Training (AI)

TL;DR

Researcher, Robustness & Safety Training (AI): Conducts state-of-the-art research on AI safety topics such as RLHF, adversarial training, and robustness, and implements new methods in core model training to launch safety improvements in OpenAI’s products. Focus on setting research directions to make AI systems safer, more aligned, and robust to adversarial use cases.

Location: Onsite in San Francisco, United States

Salary: $310,000–$460,000 + Offers Equity

Company

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

What you will do

• Conduct state-of-the-art research on AI safety topics like RLHF, adversarial training, and robustness.
• Implement new methods in core model training and launch safety improvements in OpenAI’s products.
• Set research directions and strategies to make AI systems safer, more aligned, and more robust.
• Coordinate and collaborate with cross-functional teams to ensure products meet the highest safety standards.
• Actively evaluate model and system safety, identifying risks and proposing mitigation strategies.

Requirements

• Passion for AI safety and making cutting-edge AI models safer for real-world use.
• 4+ years of experience in AI safety, especially in areas like RLHF, adversarial training, robustness, fairness & biases.
• Hold a Ph.D. or other degree in computer science, machine learning, or a related field.
• Possess experience in safety work for AI model deployment.
• In-depth understanding of deep learning research and/or strong engineering skills.
• Must be able to work onsite in San Francisco, United States.

Culture & Benefits

• Dedicated to building safe, universally beneficial AGI and deploying AI systems safely.
• Committed to fostering a culture of trust and transparency.
• Values diverse perspectives, voices, and experiences.
• Operates as an equal opportunity employer.
• Offers equity compensation.
• Fosters a collaborative work environment.