Research Engineer, Alignment Science

You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behaviour of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems, often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.

Representative projects include:

• Testing the robustness of our safety techniques by training language models to subvert our safety techniques.
• Running multi-agent reinforcement learning experiments to test out techniques like AI Debate.
• Building tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks.
• Writing scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts.
• Contributing ideas, figures, and writing to research papers, blog posts, and talks.
• Running experiments that feed into key AI safety efforts at Anthropic.

You may be a good fit if you:

• Have significant software, ML, or research engineering experience.
• Have some experience contributing to empirical AI research projects.
• Have some familiarity with technical AI safety research.
• Prefer fast-moving collaborative projects to extensive solo efforts.
• Care about the impacts of AI.

Strong candidates may also:

• Have experience authoring research papers in machine learning, NLP, or AI safety.
• Have experience with LLMs.
• Have experience with reinforcement learning.
• Have experience with Kubernetes clusters and complex shared codebases.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. We think AI systems like the ones we're building have enormous social and ethical implications, making representation even more important.

Anthropic’s compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates.

How we're different: We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. We value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles.