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Research Engineer - Scalable Interpretability
Transluce
San FranciscoOn-site1w ago
- Employment
- Full-time
About the role
- Creating diverse evaluations that range in difficulty. This involves finding naturally occurring interesting and undesirable behaviors exhibited by open-source models.
- Developing novel architectures and objectives for training interpretability assistants.
- Scaling up the training and inference pipelines to support up to 1T-scale models.
- 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
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