You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior 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 (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.

These papers give a simple overview of the topics the Alignment Science team works on: Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training, Studying Large Language Model Generalization with Influence Functions, Debating with More Persuasive LLMs Leads to More Truthful Answers, Language Models (Mostly) Know What They Know, Measuring Progress on Scalable Oversight for Large Language Models, Measuring Faithfulness in Chain-of-Thought Reasoning, Discovering Language Model Behaviors with Model-Written Evaluations.

Note: Currently, the team has a preference for candidates who are able to be based in the Bay Area. However, we remain open to any candidate who can meet the organisation's 25% in-person policy.

About Anthropic

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and for society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business and product.

Representative projects:

Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions.

Run multi-agent reinforcement learning experiments to test out techniques like AI Debate.

Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks.

Write scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts.

Contribute ideas, figures, and writing to research papers, blog posts, and talks.

Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our Responsible Scaling Policy.

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

Pick up slack, even if it goes outside your job description

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

Candidates need not have:

100% of the skills needed to perform the job

Formal certifications or education credentials

Annual Salary (USD)

The expected salary range for this position is $280k - $600k USD.

Logistics

Location-based hybrid policy: Currently, we expect all staff to be in our office at least 25% of the time.

Deadline to apply: None. Applications will be reviewed on a rolling basis.

US visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate; operations roles are especially difficult to support. But if we make you an offer, we will make every effort to get you into the United States, and we retain an immigration lawyer to help with this.

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. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Compensation and Benefits*

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.

Equity - On top of this position's salary (listed above), equity will be a major component of the total compensation. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance.

US Benefits - The following benefits are for our US-based employees:

- Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.

- Comprehensive health, dental, and vision insurance for you and all your dependents.

- 401(k) plan with 4% matching.

- 22 weeks of paid parental leave.

- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!

- Stipends for education, home office improvements, commuting, and wellness.

- Fertility benefits via Carrot.

- Daily lunches and snacks in our office.

- Relocation support for those moving to the Bay Area.

UK Benefits - The following benefits are for our UK-based employees:

- Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.

- Private health, dental, and vision insurance for you and your dependents.

- Pension contribution (matching 4% of your salary).

- 22 weeks of paid parental leave.

- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!

- Health cash plan.

- Life insurance and income protection.

- Daily lunches and snacks in our office.

* This compensation and benefits information is based on Anthropic’s good faith estimate for this position as of the date of publication and may be modified in the future. Employees based outside of the UK or US will receive a different benefits package. The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial.

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. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation based in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Research Engineer, Alignment Science

Representative projects:

You may be a good fit if you:

Strong candidates may also:

Candidates need not have:

Annual Salary (USD)

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