Joblaze summary

In this role, the Staff+ Software Engineer will design and manage backend systems that handle token processing for Claude's safety features, ensuring low latency and high reliability. Key skills include experience with high QPS systems, distributed systems, and incident management, along with a focus on graceful degradation during failures. This position is ideal for seasoned engineers with over eight years of experience, particularly those familiar with large-scale systems and machine learning models. Anthropic emphasizes collaboration and aims to create impactful AI systems, making this a critical role within a growing team.

Joblaze insights

Listed about a month ago — first seen on Joblaze September 10, 2026. Last confirmed on Anthropic's careers page October 29, 2026.
Salary band is above the typical range for AI/ML roles (median ~$190,000).
Starts above 74% of 54 comparable staff ai/ml roles in United States that list AI/ML we track (median $244,701 across 22 companies). See AI/ML salary trends
AI/ML appears in 35.3% of 283 comparable staff ai/ml roles in United States; distributed systems appears in 8.5% of 283 comparable staff ai/ml roles in United States.

Quick facts

Is the Staff+ Software Engineer, ML Sampling Path role remote?: It's hybrid — Anthropic expects some on-site time in San Francisco, CA.
What's the salary range?: Anthropic lists $320,000–$485,000 for this role.
How much experience is required?: At least 8 years of relevant experience for this Staff+ Software Engineer, ML Sampling Path role.
Where is the role based?: Anthropic is hiring for this position in San Francisco, CA.
What's the tech stack?: Joblaze extracted these technologies from the posting: AI/ML, distributed systems.
Does Anthropic sponsor work visas for this role?: Yes — the posting indicates visa sponsorship is available for the right candidate.
What seniority level is this role?: Anthropic targets staff-level candidates for this position.
Is this full-time or contract?: Full-time for this Staff+ Software Engineer, ML Sampling Path role at Anthropic.

From the original posting

About Anthropic

About the role:

The Safeguards ML Sampling Path team builds and operates the production services that power Claude's 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. You’ll 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.

What you'll do:

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.

You may be a good fit if you:

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).

Strong candidates may also have:

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

The annual compensation range for this role is listed below.

Annual Salary:

$320,000—$485,000 USD

Logistics

Standard company text repeated across Anthropic's postings is omitted here.

Staff+ Software Engineer, ML Sampling Path