Эта роль в Anthropic предлагает сильный акцент на надежности ИИ с высокой зарплатой, что делает её отличной возможностью в передовой области.
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Высокая зарплатаПередовая областьСильная миссия компанииГибридная работа
Оценка от Hirify AI
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Текст:
Hirify AI/Оригинал
TL;DR
Software Engineer, AI Reliability (AI): Improving reliability across critical AI serving paths from SDK through network, API layers, serving infrastructure, and accelerators, with an accent on designing and implementing monitoring, high-availability infrastructure, and leading incident response for large language model systems. Focus on systematic improvements, understanding system composition, and ensuring Claude's reliability for users.
Location: San Francisco, CA; New York City, NY; or Seattle, WA. Hybrid attendance is required at least 25% of the time.
Annual salary: $325,000–$485,000 USD
Company
Anthropic develops reliable, interpretable, and steerable AI systems with a focus on AI safety and societal benefit.
What you will do
Develop Service Level Objectives for large language model serving systems, balancing availability, latency, and development velocity.
Design and implement monitoring and observability across the token-serving path.
Build high-availability serving infrastructure across multiple regions and cloud providers.
Lead incident response for critical AI services, including recovery, incident reviews, and systematic improvements.
Improve the reliability of safeguard model serving in support of site reliability and AI safety.
Requirements
Strong background in distributed systems, infrastructure, reliability engineering, or SRE.
Ability to investigate unfamiliar systems during incidents and drive resolution.
Holistic understanding of system composition, interfaces, and failure points.
Strong communication, collaboration, ownership, and cross-team relationship-building skills.
Bachelor’s degree or equivalent education, training, or experience in a relevant field.
Ability to work from one of the listed US offices with at least 25% in-office attendance.
Nice to have
Experience as an SRE, Production Engineer, or in a similar reliability-focused role on large-scale systems.
Experience operating model serving or training infrastructure with more than 1,000 GPUs.
Experience with GPUs, TPUs, or Trainium, and with RDMA or InfiniBand.
Expertise in AI observability, chaos engineering, resilience testing, or open-source infrastructure and ML tooling.
Culture & Benefits
Collaborative work across research, engineering, policy, and business teams.
Flexible working hours and an office environment designed for collaboration.
Visa sponsorship is available, subject to role and candidate eligibility.
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