
Staff+ Software Engineer, Infrastructure (Distributed Systems)
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Job description
About the Position
Staff+ Software Engineer, Infrastructure (Distributed Systems)
San Francisco, CA | New York City, NY | Seattle, WA
About Anthropic
Anthropic’s 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.
About the Role
Anthropic's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models, including data pipelines, some of the largest Kubernetes clusters in the world, along with the databases, observability, and developer tooling that every other team at Anthropic depends on. As a Staff+ Software Engineer on our Infrastructure team, you'll independently scope and lead complex, multi-month infrastructure projects, make the architectural decisions other engineers build on, and work closely with research and product teams to understand their needs and build systems that keep pace as those needs evolve.
Responsibilities
- Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system
- Make architectural decisions that shape the foundation of infrastructure other engineers and teams build on
- Drive alignment on technical direction across multiple teams, working through ambiguous problem spaces
- Partner with research and product teams to understand their infrastructure and compute needs, and translate them into technical designs
- Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow
- Set technical strategy and standards for your team's infrastructure
- Build and improve operational processes, such as incident response, postmortems, and on-call rotations, that help the team learn from every incident
- Mentor other engineers and help raise the technical bar for the team
Requirements
- Experience designing, building, and operating large-scale distributed systems or infrastructure in production
- A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
- Experience making architectural decisions that other engineers and teams build on top of
- Strong software engineering fundamentals and proficiency in at least one programming language (for example, Python, Rust, Go, or Java)
- Experience with modern cloud infrastructure, including Kubernetes and infrastructure-as-code, on AWS and/or GCP
- Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders
Nice to Have
- 10+ years of software engineering experience, not including internships
- Experience with machine learning infrastructure, such as GPUs, TPUs, or Trainium, and associated networking infrastructure like NCCL
- Low-level systems experience, such as Linux kernel tuning or eBPF
- Background in security or privacy engineering best practices
- Prior experience as a technical lead or mentor for other engineers
We Offer
- Competitive compensation range: $320,000-$485,000 USD annually
- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time
- 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
- Comprehensive benefits package, including optional equity donation matching, generous vacation and parental leave, and flexible working hours
- Lovely office space in San Francisco, New York City, or Seattle
About the Company
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.
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.
© Label Your Data. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Label Your Data provides secure and high quality data annotation services for Computer Vision or NLP applications since 2020. We help Data Scientists and AI Engineers streamline the dataset labeling and focus on model development.About Label Your Data:— Founded in 2020;— 200+ annotation experts in Europe, LATAM and Africa;— 98%+ annotation accuracy benchmark;— 55 supported languages;— PCI/DSS certified;— ISO/IEC 27001:2013 certified;— GDPR, CCPA and HIPAA-compliant;— HQs in North America, EU and Asia.Our experience spans over 20 industries including Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech and Insurance.Our core services include but are not limited to:— Image & video annotation: 2D boxes, OCR, object/action detection, polygons, key points, semantic segmentation, 3D cuboids;— Text annotation: classification, NER, intent & sentiment analysis, prompts creation, Q&A pairs generation;— Audio annotation: transcription, sentiment recognition;— Sensor data annotation;— Data classification & categorization;— Data entry;— Data collection;— Model validation.
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