Member of Technical Staff - Safety

Highlights

• Own red-teaming and adversarial evaluation pipeline for open models.
• Build dynamic automated safety benchmarks that evolve with capabilities.
• Serve as gatekeeper validating releases meet risk thresholds before shipping.

What they offer

• Top-tier compensation: salary and equity structured to recognize and retain talent globally
• Stock options for all contributors
• Comprehensive medical, dental, vision, and life, with annual wellness allowance
• Lunch and dinner provided in the office daily
• 22 weeks paid parental leave for all new parents
• Unlimited paid time off in the U.S. and 30 days in the U.K.
• Regular off-sites, happy hours, and team celebrations

Ideal candidate

High-agency safety researcher who thrives in fast startups and cares about open intelligence. You enjoy adversarial probing, making high-stakes release calls, and turning findings into reliable guardrails.

Requirements

• Graduate degree (MS or PhD) in Computer Science, Machine Learning, or related discipline, or equivalent practical experience in AI Safety
• Deep technical understanding of LLM safety, including adversarial attacks, red-teaming methodologies, and interpretability
• Strong software engineering capabilities with experience building automated evaluation pipelines or large-scale ML systems
• Experience with Reinforcement Learning (RLHF/RLAIF) and how it impacts model safety and alignment is a strong plus
• Thrive in a fast-paced, high-agency startup environment with bias toward action
• Willing to make high-stakes decisions regarding model release and safety thresholds
• Passionate about advancing the frontier of intelligence