Job Information
Anthropic PBC Research Engineer, AI Observability in San Francisco, California
Responsibilities:
Design and implement AI-based monitoring systems for AI training and deployment
Extend and improve core frameworks for processing large volumes of unstructured text
Partner with researchers and safety teams across Anthropic to understand their analytical needs and build solutions
Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings
Contribute to the strategic direction of the team, including decisions about what to build, what to partner on, and where to invest
You May Be a Good Fit If You:
Have 5+ years of software engineering experience, with meaningful exposure to ML systems
Are excited about the problem of scaling human oversight of AI systems
Are familiar with LLM application development (context engineering, evaluation, orchestration)
Enjoy building tools that other people use you care about UX, reliability, and documentation
Can context-switch between deep infrastructure work and user-facing product thinking
Thrive in collaborative, cross-functional environments
Strong Candidates May Also Have:
Research experience in AI safety, alignment, or responsible deployment
Practical experience with both data science and engineering, including developing and using large-scale data processing frameworks
Experience with productionizing internal tools or building developer-facing platforms
Background in building monitoring or observability systems
Comfort with ambiguity our team is small and growing, and you'll help define what we become
The annual compensation range for this role is listed below.
For sales roles, the range provided is the roles On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000-$405,000USD
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.
Your safety matters to us.To protect yourself from potential scams, remember that Anthropic recruiters only contact you from@anthropic.comemail 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 linksvisit
anthropic.com/careers{target="_blank"}directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research ill 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 and Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.