San Francisco, California, United States · Hybrid
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · Hybrid
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · On-site
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San Francisco, California, United States · Hybrid
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Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to t…
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San Francisco, California, United States · Hybrid
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Skills: Systems Engineering, Backend Development, People Management, Rust, Performance Optimization
San Francisco, California, United States · Hybrid
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About Gusto At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in D…
Skills: Full-stack Engineering, AI/LLM Integration, Product Engineering, Technical Leadership, Mentorship
San Francisco, California, United States · Hybrid
$164k–$193k/yr
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the glo…
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San Francisco, California, United States · On-site
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Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely import…
Skills: React, TypeScript, Python, Full-Stack Engineering, Project Leadership
San Francisco, California, United States · Hybrid
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At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew. We seek to ignite that passion by setting high standards, championing teamwork, and creating work-lif…
Skills: Enterprise Security, Network Security, Endpoint Security, SaaS Security, SIEM
San Francisco, California, United States · Hybrid
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About Mesh At Mesh, our mission is to enable consumers to pay and be paid with any asset. Today, trillions of dollars in tokenized assets exist but remain largely unusable for everyday commerce. Mesh is bridging this gap…
Skills: TypeScript, React, Redux, C#, Node.js
San Francisco, California, United States · On-site
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About Patronus AI Patronus AI is a frontier lab developing simulation research and infrastructure to accelerate progress toward human-aligned AGI. We are on a mission to simulate all of the world’s intelligence. We are t…
Skills: React, TypeScript, Next.js, Python, SQLite
San Francisco, California, United States • Hybrid
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Build and scale the infrastructure and data pipelines used for Safeguards machine learning research to detect AI misuse. Own the training, evaluation, and scoring workflows to accelerate the research loop and ensure production-grade reliability.
Requires strong software engineering fundamentals in Python and experience building production-grade distributed or data-intensive systems. Candidates should be comfortable working across the entire pipeline from exploratory research experiments to deployment.
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.
Anthropic's Safeguards team builds the systems that detect and mitigate misuse of our AI models, from individual policy violations to sophisticated, coordinated attacks. A growing part of that work depends on lightweight detection methods trained on model internals, which let us identify harmful behavior cheaply and at scale. This work feeds directly into Anthropic's Responsible Scaling Policy commitments.
We're looking for an engineer to own the infrastructure behind that research. This is the tooling our researchers rely on to run experiments, train detection methods, and select detections for launch. It sits between research and production: researchers depend on it for fast iteration, and our detection systems depend on it for reliable, correct results as our models continue to change.
Running machine learning workloads at our scale often requires solving novel systems problems. You'll identify those problems and build the abstractions, pipelines, and tooling that keep the research loop fast as requirements shift underneath you. Strong candidates will have a track record of solving large-scale systems and data problems and will be excited to grow deep machine learning expertise alongside it.
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
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.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.
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.
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.
Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems.
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
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