Staff+ Software Engineer, Infrastructure, Interpretability

Responsibilities:</h2> <ul> <li> <p>Design, build, and own shared infrastructure for Interpretability - research environments, data systems, and compute tooling that researchers rely on daily</p> </li> <li> <p>Lead cross-team efforts with our <a href="https://www.anthropic.com/institute/recursive-self-improvement" target="_blank">agentic engineering</a>, security, compute, and storage platform teams, so that company-wide solutions serve research needs</p> </li> <li> <p>Discover and resolve major organization-wide developer experience issues</p> </li> <li> <p>Help take interpretability methods from research code to dependable audit pipelines</p> </li> </ul> <h2>You may be a good fit if you:</h2> <ul> <li> <p>Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python</p> </li> <li> <p>Have significant experience building and operating secure and scalable software infrastructure - cloud systems, distributed systems, or developer tooling</p> </li> <li> <p>Have strong cross-functional communication skills - equally at home working with researchers and with platform and security teams</p> </li> <li> <p>Are extremely curious about unfamiliar domains</p> </li> <li> <p>Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions</p> </li> <li> <p>Are curious about interpretability research and its role in AI safety (though no research experience is required!)</p> </li> <li> <p>Care about the societal impacts and ethics of your work</p> </li> </ul> <h2>Strong candidates may also have:</h2> <ul> <li> <p>Experience with cloud infrastructure (e.g. GCP or AWS), Kubernetes, networking and infrastructure-as-code</p> </li> <li> <p>Security engineering experience: identity / auth / access management, sandboxing, red teaming</p> </li> <li> <p>Experience with data warehousing, large-scale storage systems, and data lifecycle management - especially for research</p> </li> <li> <p>Experience with compute schedulers and accelerator fleet management</p> </li> <li> <p>Experience building developer productivity tooling and observability stacks</p> </li> <li> <p>Experience building tooling to accelerate research teams</p> </li> </ul> <h2>Representative Projects:</h2> <ul> <li> <p>Design and stand up a hardened research environment where researchers experiment directly on frontier model weights</p> </li> <li> <p>Build lifecycle management for petabytes of research data - visibility, retention, and cost efficiency</p> </li> <li> <p>Build self-serve scheduling and capacity tooling</p> </li> <li> <p>Create the observability that catch infrastructure regressions before they cost researchers valuable time</p> </li> </ul> <h2>Role Specific Location Policy:</h2> <ul> <li> <p>This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.</p> </li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>The annual

compensation range for this role is listed below. </p> <p>For sales roles, the range provided is

the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for

the role.</p></div><div class="title">Annual Salary:</div><div class="pay-range"><span>$320,000</span><span class="divider">—</span><span>$485,000 USD</span></div></div></div><div class="content-conclusion"><h2><strong>Logistics</strong></h2> <p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p> <p><strong>Required field of study: </strong>A field relevant to

the role as demonstrated through coursework, training, or professional experience</p> <p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level

requirements for the position</p> <p><strong>Location-based hybrid policy:</strong> 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.</p> <p><strong data-stringify-type="bold">Visa sponsorship:</strong> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But 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.</p> <p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br><br><strong data-stringify-type="bold">Your safety matters to us.</strong> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit <u data-stringify-type="underline"><a class="c-link c-link--underline" href="http://anthropic.com/careers" target="_blank" data-stringify-link="http://anthropic.com/careers" data-sk="tooltip_parent" data-remove-tab-index="true">anthropic.com/careers</a></u> directly for confirmed position openings.</p> <h2><strong>How we're different</strong></h2> <p>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.</p> <p>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.</p> <h2><strong>Come work with us!</strong></h2> <p>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. <strong data-stringify-type="bold">Guidance on Candidates' AI Usage:</strong> Learn about <a class="c-link" href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" data-stringify-link="https://www.anthropic.com/candidate-ai-guidance" data-sk="tooltip_parent">our policy</a> for using AI in our application process.</p></div>

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