Job description
Trajectory Labs • San Francisco Bay Area
Expression of interest
About us
Our mission is to automate AI safety, to pave the way for a future where the vast majority of AI safety work is done by AI models.
To that end, 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 its cyber safeguards and have it generate a working exploit), led Anthropic's prompt injection evaluation of Auto mode, and been featured in 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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