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Senior / Staff Engineer, Inference

Senior / Staff Engineer, Inference

Menlo VenturesSan Francisco, CA, United States
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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 :

Our Scalability and Capability Inference team is responsible for building and maintaining the critical systems that serve our LLMs to a diverse set of consumers. As the cornerstone of our service delivery, the team focuses on scaling inference systems, ensuring reliability, optimizing compute resource efficiency, and developing new inference capabilities. The team tackles complex distributed systems challenges across our entire inference stack, from optimal request routing to efficient prompt caching.

You may be a good fit if you :

  • Have significant software engineering experience
  • Are results-oriented, with a bias towards flexibility and impact
  • Pick up slack, even if it goes outside your job description
  • Enjoy pair programming (we love to pair!)
  • Want to learn more about machine learning research
  • Care about the societal impacts of your work

Strong candidates may also have experience with :

  • High performance, large-scale distributed systems
  • Implementing and deploying machine learning systems at scale
  • LLM optimization batching and caching strategies
  • Kubernetes
  • Python
  • Representative projects :

  • Optimizing inference request routing to maximize compute efficiency
  • Autoscaling our compute fleet to effectively match compute supply with inference demand
  • Contributing to new inference features (e.g. structured sampling, fine tuning)
  • Supporting inference for new model architectures
  • Ensuring smooth and regular deployment of inference services
  • Analyzing observability data to tune performance based on production workloads
  • Deadline to apply : None. Applications will be reviewed on a rolling basis.

    The expected salary range for this position is :

    Annual Salary :

    $300,000 — $405,000 USD

    Logistics

    Education 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 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.

    #J-18808-Ljbffr

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