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Member of Technical Staff - Mechanistic Interpretability

Vmax· Research and Engineering
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SF$300k - $500kFull-timePosted 3mo ago

About the role

Role focused on applying mechanistic interpretability to extract training signals from LLM internal states and develop intrinsic rewards for reinforcement learning, advancing open-ended learning at Vmax.

Responsibilities

  • Develop methods for using mechanistic interpretability to extract useful training signals from the internal states of language models.
  • Turn representations, features, circuits, and causal model behaviors into intrinsic rewards for reinforcement learning.
  • Compare interpretability-derived rewards against human feedback, learned reward models, verifiers, and task-level outcome rewards.
  • Design metrics and baselines for reward quality, including alignment with intended behavior, generalization across tasks, robustness, and resistance to reward hacking.
  • Investigate how internal representations evolve during RL and post-training, and use these insights to improve training objectives.
  • Develop infrastructure for reproducible, large-scale experiments on LLM agents, interpretability tools, and RL environments.
  • Define and pursue a high-impact research agenda that advances Vmax’s goal of open-ended learning beyond imitation of human expertise.

Qualifications

  • PhD or equivalent experience in machine learning, reinforcement learning, or a closely related field.
  • Track record of research excellence, as demonstrated by publications, open source work, deployed AI systems, or other substantial technical contributions.
  • Deep understanding of modern machine learning, especially reinforcement learning, representation learning, and large language models.
  • Strong familiarity with LLM post-training methods
  • Experience designing and running rigorous ML experiments, including ablations, baselines, evaluation design, and failure analysis.
  • Expertise with Python and at least one major ML framework such as PyTorch or JAX.
  • Ability to work independently on open-ended research problems and turn ambiguous ideas into concrete experimental programs.

Skills

Required:PhD or equivalent in ML/RL or related fieldRL experimentation and evaluation designPython and ML frameworks (PyTorch or JAX)
Nice to have:Mechanistic interpretabilityCommunication of technical results
Last updated Jul 5, 2026. Interested? Apply on the company site.
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About Vmax

Vmax is developing AI capable of open-ended learning. We build systems that exceed human performance across every domain, optimizing beyond the local maxima of learning from human expertise.

Vmax is automating reinforcement learning. We transform proprietary data and evals into new sets of environments. We refine agents on new examples of the tasks they are intended to perform.

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