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Engineering Manager, Cloud Inference

Engineering Manager, Cloud Inference

GenAI JobsSan Francisco, CA, United States
6 days ago
Job type
  • Full-time
Job description

# Engineering Manager, Cloud InferenceAnthropicSan Francisco, CA### About the RoleAbout AnthropicAnthropic’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 roleWe are seeking an experienced Engineering Manager to lead the Cloud Inference Capacity & Operations team for Vertex. You will lead your team to scale and optimize Claude to serve the massive audiences of developers and enterprise companies using GCP. You and your team will optimize the consumption of accelerators. Our team ensures our LLMs meet rigorous performance, safety and security standards and enhance our core infrastructure for packaging, testing, and deploying inference technology across the globe. Your work will increase the scale at which our services can operate and accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms.Responsibilities :

  • Set technical strategy and oversee development of high scale, reliable infrastructure systems
  • Collaborate across teams across companies to deeply understand infrastructure, operations and capacity needs, identifying potential solutions to support frontier LLM serving
  • Create clarity for the team and stakeholders in an ambiguous and evolving environment
  • Take an inclusive approach to hiring and coaching top technical talent, and support a high performing team
  • Design and run processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twiceYou may be a good fit if you :
  • Have 10+ years of experience in high-scale, high-reliability software development, particularly infrastructure or capacity management
  • Have 3+ years of engineering management experience
  • Have experience recruiting, scaling, and retaining engineering talent in a high growth environment
  • Have experience scaling resources and operations to accommodate rapid growth
  • Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
  • Excel at building strong relationships with stakeholders at all levels and across companies
  • Enjoy working in a fast-paced, early environment; comfortable with adapting priorities as driven by the rapidly evolving AI space
  • Have excellent written and verbal communication skills and comfort with a high degree of collaboration with both internal and external engineers and product managers
  • Demonstrated success building a culture of belonging and engineering excellence
  • Are motivated by developing AI responsibly and safelyStrong candidates may also have experience with :
  • Machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
  • Deployment and capacity management automation
  • Security and privacy best practice expertiseThe expected salary range for this position is : Annual Salary : $320,000—$485,000 USDLogisticsEducation requirements : We require at least a Bachelor's degree in a related field or equivalent experience.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.How we're differentWe 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### Requirements
  • Machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
  • Deployment and capacity management automation
  • Security and privacy best practice expertise### Cookie Consent.

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