Privacy Research Engineer, Safeguards

About Anthropic 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\u2019ll 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 You may be a good fit if you have 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. Annual Salary: $320,000 — $485,000 USD Logistics Education requirements: We require at least a Bachelor\u2019s 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 do sponsor visas. However, we aren\u2019t able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, 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\u2019re interested in this work. We think AI systems like the ones we\u2019re 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. How we\u2019re 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 orwarding our long-term goals of steerable, trustworthy AIurther rather than working on smaller, more specific puzzles. We view AI research as an empirical science with elements of physics and biology, as well as computer science. We are highly collaborative and host frequent research discussions to ensure we pursue the highest-impact work. We greatly value communication skills. 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 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. Guidance on Candidates\u2019 AI Usage: Learn about our policy for using AI in our application process #J-18808-Ljbffr Menlo Ventures