Staff+ Software Engineer, ML Sampling Path

Anthropics 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.

The Safeguards ML Sampling Path team builds and operates the production services that power Claudes safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them and each millisecond of added latency is wait time for our users. Youll keep p99 latency flat as traffic grows build for robustness as dependencies time out or partially fail and ship changes safely to a system that cannot go down.

• Design build and operate the backend systems that process every token on the generation path for Claude requests including the streaming contract with the API and inference engines.
• Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency time-to-first-token and availability and lead incident response and postmortem follow-through.
• Ship changes to the hot path rapidly but safely canaried and gradual rollouts error budget and latency gating fast rollbacks and drive per-token performance: chase tail latency and keep cost flat as traffic models and checks per request grow.
• Set technical direction for the sampling path: lead design reviews make latency reliability and cost trade-off calls with the inference and research teams mentor engineers and raise the operational bar for the wider Safeguards organization.

• Have designed built and operated high QPS systems at global scale and were accountable for them in production: incident response outages and postmortem-driven remediation.
• Have a strong foundation in distributed systems: replication consistency tradeoffs failure modes and SLO management under load.
• Design systems for graceful degradation: you plan for a slow dependency a dropped stream or a half-rolled-out deploy before it happens and build so the system degrades predictably instead of failing.
• Have successfully shipped broad or all-encompassing changes to mission critical systems (e.g. database migrations interface changes rewrites).

• 8 years of industry software engineering experience.
• Familiarity with LLM inference systems and transformer-based models (not required but a plus).

Minimum education: Bachelors degree or an equivalent combination of education training and/or experience

Required field of study:A field relevant to the role as demonstrated through coursework training or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

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 arent 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.

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 youre interested in this work. We think AI systems like the ones were 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.

Your safety matters to us. To protect yourself from potential scams remember that Anthropic recruiters only contact you 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 youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

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. Were 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.

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.

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 AI Usage:Learn aboutour policy for using AI in our application process.