Anthropic
Privacy Research Engineer, Safeguards
Anthropic, San Francisco, California, United States, 94199
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role We are looking for researchers to help mitigate the risks that come with building AI systems. One of these risks is the potential for models to interact with private user data. In this role, you'll design and implement privacy‑preserving techniques, audit our current techniques, and set the direction for how Anthropic handles privacy more broadly.
Responsibilities
Lead our privacy analysis of frontier models, carefully auditing the use of data and ensuring safety throughout the process
Develop privacy‑first training algorithms and techniques
Develop evaluation and auditing techniques to measure the privacy of training algorithms
Work with a small, senior team of engineers and researchers to enact a forward‑looking privacy policy
Advocate on behalf of our users to ensure responsible handling of all data
Qualifications
Experience working on privacy‑preserving machine learning
A track record of shipping products and features inside a fast‑moving environment
Strong coding skills in Python and familiarity with ML frameworks like PyTorch or JAX.
Deep familiarity with large language models, how they work, and how they are trained
Have experience working with privacy‑preserving techniques (e.g., differential privacy and how it is different from k‑anonymity, l‑diversity, and t‑closeness)
Experience supporting fast‑paced startup engineering teams
Demonstrated success in bringing clarity and ownership to ambiguous technical problems
Proven ability to lead cross‑functional security initiatives and navigate complex organizational dynamics
Strong Candidates May Also
Have published papers on the topic of privacy‑preserving ML at top academic venues
Prior experience training large language models (e.g., collecting training datasets, pre‑training models, post‑training models via fine‑tuning and RL, running evaluations on trained models)
Prior experience developing tooling to support privacy‑preserving ML (e.g., differential privacy in TF‑Privacy or Opacus)
Compensation The expected base compensation for this position is below. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.
$320,000 - $485,000 USD
Logistics Education requirements:
We require at least a Bachelor's degree in a related field or equivalent experience.
Location‑based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We sponsor visas. However, we can't sponsor every role for every candidate. But if we make you an offer, we'll make reasonable effort to get you a visa.
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.
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.
Come Work with Us! Anthropic is a public benefit corporation headquartered 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.
#J-18808-Ljbffr
About the Role We are looking for researchers to help mitigate the risks that come with building AI systems. One of these risks is the potential for models to interact with private user data. In this role, you'll design and implement privacy‑preserving techniques, audit our current techniques, and set the direction for how Anthropic handles privacy more broadly.
Responsibilities
Lead our privacy analysis of frontier models, carefully auditing the use of data and ensuring safety throughout the process
Develop privacy‑first training algorithms and techniques
Develop evaluation and auditing techniques to measure the privacy of training algorithms
Work with a small, senior team of engineers and researchers to enact a forward‑looking privacy policy
Advocate on behalf of our users to ensure responsible handling of all data
Qualifications
Experience working on privacy‑preserving machine learning
A track record of shipping products and features inside a fast‑moving environment
Strong coding skills in Python and familiarity with ML frameworks like PyTorch or JAX.
Deep familiarity with large language models, how they work, and how they are trained
Have experience working with privacy‑preserving techniques (e.g., differential privacy and how it is different from k‑anonymity, l‑diversity, and t‑closeness)
Experience supporting fast‑paced startup engineering teams
Demonstrated success in bringing clarity and ownership to ambiguous technical problems
Proven ability to lead cross‑functional security initiatives and navigate complex organizational dynamics
Strong Candidates May Also
Have published papers on the topic of privacy‑preserving ML at top academic venues
Prior experience training large language models (e.g., collecting training datasets, pre‑training models, post‑training models via fine‑tuning and RL, running evaluations on trained models)
Prior experience developing tooling to support privacy‑preserving ML (e.g., differential privacy in TF‑Privacy or Opacus)
Compensation The expected base compensation for this position is below. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.
$320,000 - $485,000 USD
Logistics Education requirements:
We require at least a Bachelor's degree in a related field or equivalent experience.
Location‑based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We sponsor visas. However, we can't sponsor every role for every candidate. But if we make you an offer, we'll make reasonable effort to get you a visa.
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.
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.
Come Work with Us! Anthropic is a public benefit corporation headquartered 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.
#J-18808-Ljbffr