Research Engineer / Research Scientist, Finetuning

You want to help construct and rapidly iterate on machine learning experiments to help us improve the behavior of powerful AI systems through finetuning. You care about making AI helpful, honest, and harmless, and are interested in shaping model behavior to be more aligned with human values and goals. You could describe yourself as both a scientist and an engineer. As a Research Scientist or Research Engineer on the Finetuning team, you'll contribute to research on improving language models through techniques like constitutional AI. You will have the opportunity to do creative, cutting-edge research on frontier models, and to see your work result in concrete improvements in performance and safety.

We generally expect research scientists to be able to iterate on their own experiments. We also provide opportunities for engineers to pursue their own research projects. Therefore this role can be more research oriented or more engineering oriented, depending on the experience and interests of the candidate.

Representative projects

• Help develop novel finetuning techniques to improve language model behavior and make models more helpful, honest, and harmless.
• Test out techniques like constitutional AI at scale and measure their impacts on model behavior.
• Build tooling and infrastructure to enable efficient fine-tuning experiments on large language models.
• Develop novel prompts and prompting strategies to improve and test model behaviours.
• Run experiments that feed into key AI research and safety efforts at Anthropic.

You may be a good fit if you

• Have significant Python, machine learning, research engineering, or research experience.
• Prefer fast-moving collaborative projects with concrete goals that involve improving model behaviours.
• Are results-oriented, with a bias towards flexibility and impact.
• Pick up slack, even if it goes outside your job description.
• Care about the impact of AI and of your work.

Strong candidates may also

• Have prior experience with large language model finetuning techniques such as RLHF.
• Have experience with complex shared codebases and RL infrastructure.
• Have experience authoring research papers in machine learning, NLP, or AI alignment or similar industry experience.

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

• 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

• 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.