Research Engineer, Interpretability Systems

Location: San Francisco Bay Area, on-site

Salary: $250,000–$350,000 per year

Company

Early-stage AI research lab founded by former frontier-model researchers and focused on alignment and interpretability for large language models.

What you will do

• Build custom RL-style environments and experimental testbeds for interpretability research.
• Develop tooling for activation tracing, concept detection, and mechanistic analysis of model representations.
• Implement probes for latent concepts such as deception, uncertainty, goals, and hidden objectives.
• Prototype activation-level steering methods beyond prompting and fine-tuning.
• Collaborate with researchers to iterate from research ideas to implementations, experiments, and results.
• Define benchmarks and measurement frameworks for model consistency, robustness, alignment, and interpretability.

Requirements

• Strong software engineering fundamentals and experience building experimental machine learning systems.
• Experience working with model internals, representations, or post-training systems.
• Strong Python skills and experience with deep learning frameworks, preferably PyTorch.
• Ability to rapidly prototype and iterate in open-ended research environments.
• Experience in interpretability, alignment, or machine learning research is preferred.
• A PhD is considered ideal.

Culture & Benefits

• Early-stage research environment focused on cutting-edge alignment and interpretability work.
• Close collaboration between research engineers and researchers.
• Opportunity to build infrastructure enabling new classes of model understanding and control experiments.