The Alignment Research Center (ARC) is a non-profit whose mission is to align future machine learning systems with human interests. The high-level agenda of the Theory team (not to be confused with the Evals team, which has now spun out as METR) is described by the report on Eliciting Latent Knowledge (ELK): roughly speaking, we’re trying to design ML training objectives that incentivize systems to honestly report their internal beliefs.

For the last couple of years, we’ve mostly been focused on an approach to ELK based on formalizing a kind of heuristic reasoning that could be used to analyze neural network behavior. You can read more about this approach in some of our recent blog posts, such as:

- Formal verification, heuristic explanations and surprise accounting

- Estimating tail risk in neural networks

- Formalizing the presumption of independence

Our research has reached a stage where we’re coming up against concrete problems in mathematics, theoretical computer science and machine learning, and so we’re particularly excited about hiring researchers with relevant background, regardless of whether they have worked on AI alignment before.

We currently have two hiring streams, which are respectively looking for:

- People who have a strong theoretical background (in math, physics or computer science, for example)

- People who have some theoretical background and some empirical machine learning background

We also remain open to anyone who is excited about getting involved in AI alignment, even if they do not have an existing research record.

Ultimately, we are excited to hire people who could contribute to our research agenda. One way to figure out whether you might be able to contribute would be to take a look at some of our recent research, as described on our blog.

ARC’s Theory team currently has 6 permanent team members (see our team here), alongside a varying number of temporary team members (recently anywhere from 0–3).

Most of the time, team members work on research problems independently, with frequent check-ins with their research advisor (e.g., twice weekly). This work is often somewhat similar to academic research in pure math or theoretical computer science.

In addition to this, we also allocate a significant portion of our time to higher-level questions surrounding research prioritization, which we often discuss at our weekly group meeting. Since the team is still small, we are keen for new team members to help with this process of shaping and defining our research.

ARC shares an office with several other groups working on AI safety such as METR and Redwood Research, so even though the Theory team is small, the office is lively with lots of AI-related discussion.

Our current interview process has two streams, a theoretical stream and a machine learning stream.

The theoretical stream involves:

- 3-hour take-home test involving math and computer science puzzles

- 30-minute non-technical phone call

- 1-day onsite interview

The machine learning stream is still being developed, but will likely follow a broadly similar format.

We will compensate candidates for their time when this is logistically possible.

ARC is based in Berkeley, California, and we would prefer people who can work full-time from our office, but we are open to discussing remote or part-time arrangements in some circumstances. We can sponsor visas and are H-1B cap-exempt.

We are accepting applications for both visiting researcher (1–3 months) and full-time positions. The intention of the visiting researcher position is to assess potential fit for a full-time role, and we expect to invite around one third to one half of visiting researchers to join full-time. We are also able to offer straight-to-full-time positions, but we anticipate that we will only be able to do this for people with a legible research track-record. We are currently only interested in applicants who can start before Jun 30, 2026.

Salaries are in the $150k–400k range for most people depending on experience.

If you have any questions about anything in this posting, please email hiring@alignment.org.

If you want to provide any feedback, you can use this form: https://forms.gle/DndeoBekS6ViyifW6