Staff+ Software Engineer, Inference Runtime

requirements, and making the call on build vs. adopt Mentor engineers on

the team through design review, code review, and direct collaboration, raising the technical bar without owning headcount Minimum

qualifications Deep background in systems engineering or ML infrastructure, with the ability to go hands-on with performance profiling, latency and throughput optimization, and systems debugging at scale Real depth in at least one accelerator ecosystem (CUDA/GPU, TPU, or Trainium/AWS Neuron) and genuine appetite to keep the runtime agnostic across all of them Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users A track record of defining and using engineering metrics to drive improvement: you've set SLOs on platform surfaces, and driven escape rates, release times, latency, or throughput in a measurable direction Experience driving technical alignment across organizational boundaries, advocating for your team's needs while contributing to shared infrastructure Strong written and verbal communication, and the ability to influence technical direction without formal authority Preferred

qualifications 8+ years of software engineering experience, with significant time as the technical lead or anchor on a platform, inference runtime, or ML infrastructure team Experience with ML compiler toolchains (XLA, Triton, NeuronX) or accelerator driver/firmware management at scale Background operating production as a validation surface at scale: shadow traffic, canary populations, automated baseline comparison, fast rollback Experience with deterministic or simulation-based testing for hardware-dependent systems Experience with CI/CD systems at scale, particularly for workloads involving accelerator hardware Familiarity with Kubernetes-based development and job scheduling environments Prior tech lead experience on a developer productivity or platform engineering team at a fast-growing AI/ML company The annual

compensation range for this role is listed below. 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. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s 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 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. 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. 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. Your safety matters to us. 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 anthropic.com/careers directly for confirmed position openings. 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. 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' AI Usage: Learn about our policy for using AI in our application process.

A meeting lands on your calendar

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