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.
Responsibilities- Build machine learning models to detect unwanted or anomalous behaviors from users and API partners, and integrate them into our production system
- Improve our automated detection and enforcement systems as needed
- Analyze user reports of inappropriate accounts and build machine learning models to detect similar instances proactively
- Surface abuse patterns to our research teams to harden models at the training stage
Requirements
- Have 4+ years of experience in a data scientist, research scientist, or research/ML engineering position, preferably with a focus on trust and safety.
- Have proficiency in SQL, Python, and data analysis/data mining tools.
- Have proficiency in building trust and safety AI/ML systems, such as behavioral classifiers or anomaly detection.
- Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
- Care about the societal impacts and long‑term implications of your work.
Bonus Qualifications
- Have experience with machine learning frameworks like Scikit‑Learn, Tensorflow, or Pytorch
- Have experience with full stack engineering to build internal tooling
- Have experience with high performance, large‑scale ML systems
- Have experience with language modeling with transformers
- Have experience with reinforcement learning
- Have experience with large‑scale ETL
Annual Salary
The expected salary range for this position is $300k - $450k USD.
Hybrid Policy & Visa SponsorshipCurrently, we expect all staff to be in our office at least 25% of the time. 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 or United Kingdom, and we retain an immigration lawyer to help with this.
Compensation and BenefitsAnthropic’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.
EquityOn 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.
Benefits Notes
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.
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