Job description
Trajectory Labs • San Francisco Bay Area
Expression of interest
About us
Our mission is to automate AI safety and security evaluation, to pave the way for a future where the vast majority of AI safety research is done by AI models.
Frontier models already solve coding problems that take humans days, but models still cannot do much of the hard-to-supervise fuzzy tasks that matter for AI safety and security. In order to train models to reliably do those tasks, we build safety and alignment evals, red-teaming programs, and RL environments for frontier AI labs.
Although Trajectory is less than a year old, we have already been featured in Anthropic's Fable 5 & Mythos 5 System Card (the only external team to bypass the cyber safeguards), the Opus 5 System Card, and Meta's Muse Spark Safety & Preparedness Report.
This is an early-stage startup role, so you should expect and enjoy being in a role where responsibilities can grow and priorities can quickly change.
We don't have a specific role open right now, but we're always looking for exceptional people. Tell us who you are and we'll reach out when there's a fit.
About you
Essential
- Impact-driven: you want to improve the safety of frontier AI systems.
- Agent-native engineering: you use coding agents and LLMs as core development tools.
- Autonomy and judgment: you can turn a vague research objective into a concrete plan, make good trade-offs, and keep the work moving with minimal direction.
- Early-stage startup drive: you enjoy a fast pace, shifting priorities, limited structure, and taking on whatever is most important to help the company succeed.
Desirable
- Experience working in an AI safety or alignment context
- Experience building evals, red-teaming systems, RL environments, or model-training data
- Experience collaborating with frontier labs or other demanding technical customers
These criteria are a guide, not a checklist. If you want to do your life's work making frontier models safer and this role excites you, we encourage you to apply.
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