Research Engineer - Scalable Interpretability
About The Position
Transluce is a non-profit research lab building tools for scalable, end-to-end oversight of AI systems. We build world-class, AI-backed analysis tools and use these to set industry standards for evaluation. Our tools are integrated with core agent benchmarks like SWE-bench, while our evaluations are directly underpinning regulation, including our role as EU AI Office’s main evaluation developer for harmful manipulation risks. We are looking for strong scientists and engineers to help advance our vision of scalable end-to-end oversight assistants, building on our recent advances such as predictive concept decoders and user model extractors. As part of our highly collaborative team, you will learn and grow quickly, creating technology at the frontier of AI research and with high direct impact.
Requirements
- Experience with fine-tuning language models, designing new architectures, and creating evaluations.
- Reliable results: good experimental design, epistemic self-awareness and transparency.
- Generativeness: coming up with original, productive ideas for unblocking progress.
- Curiosity: a desire to understand ML systems and how they work.
- Strong programming ability, including navigating trade-offs between prototyping speed and maintainability.
- Strong communication skills, low ego, openness to giving and receiving feedback.
Responsibilities
- Help develop and train scalable interpretability assistants that can predict and detect unexpected and subtle behaviors from models’ activations.
- Create diverse evaluations that range in difficulty, finding naturally occurring interesting and undesirable behaviors exhibited by open-source models.
- Develop novel architectures and objectives for training interpretability assistants.
- Scale up the training and inference pipelines to support up to 1T-scale models.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
