Software Engineer, Claude.AI

Sorry, this job was removed at 06:18 p.m. (CST) on Monday, Jan 13, 2025
2 Locations
In-Office
300K-405K Annually
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
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:

We are looking for a software engineer to join our Claude.AI product team and help build innovative interfaces and APIs that enable powerful interactions with advanced language models. At Anthropic, we're not just building AI tools; we're reinventing how machines work with humans! You will work with a talented team of engineers, researchers, design and Product teams  to design and implement key components of our product and platform, pushing the boundaries of what's possible with AI-powered tools.

We have multiple roles open on this team and are looking for experienced engineers at different stages in their career who are excited about this space and our mission.

Responsibilities:
  • Develop powerful solutions that leverage the power of language models to streamline tasks and boost productivity
  • Optimize the API and interfaces for performance, scalability, and an intuitive user experience
  • Personalize the experience to ensure accessibility and a seamless integration in people’s day to day work
  • Collaborate with researchers to continuously improve interfaces based on real-world user interactions and feedback
  • Implement tools and processes to monitor model behavior, performance, and alignment with user needs
  • Contribute to the development of novel human-machine interaction paradigms that redefine how we work with AI
You might be a good fit if you:
  • Have 5+ years of experience as a software engineer, preferably building APIs and/or interfaces
  • Have strong practical coding skills, ideally in React or other frontend languages/technologies, and experience with service-oriented architectures 
  • Take a user-centric approach to product development, prioritizing solutions that are robust, scalable, accessible, and intuitive
  • Are passionate about the potential of AI to revolutionize the way we work and eager to tackle cutting-edge challenges in human-machine collaboration
  • Have 0 to 1 experience with a proclivity towards shipping and learning, while balancing a high quality bar
  • Thrive in a fast-paced, collaborative environment and and enjoy working closely with cross functional partners and teammates 
Strong candidates may also:
  • Have experience with REST APIs
  • Have experience with containerization and DevOps
  • Have experience with QA and testing automation
  • Have experience with privacy and security best practices
  • Possess a vision for the future of human-machine interaction and a drive to make that vision a reality

If you're excited by the prospect of shaping the future of human-AI collaboration and creating groundbreaking technologies that empower people to achieve more, we'd love to hear from you. Join us on our mission to unlock the full potential of human-machine synergy and redefine the nature of work itself.

The expected salary range for this position is:

Annual Salary:

$300,000$405,000 USD

Logistics

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.

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The Company
HQ: San Francisco, California
57 Employees

What We Do

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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