Research Engineer, Data Ingestion

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 an experienced Research Engineer to join the Data Ingestion team, which owns the problem of acquiring all of the available data on the internet through a large scale web crawler. Most of Anthropic's research and product builds on top of the best pretrained models that we can produce, which in turn rely on having the best pretraining data. This role combines hands-on engineering with data research—you'll build and scale our crawler infrastructure while also conducting experiments to evaluate and improve data quality. Successfully scaling our data corpus is critical to our continued efforts at producing the best pretrained models.

Responsibilities:

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Develop and maintain our large-scale web crawler

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Design and run experiments to evaluate data quality, extraction methods, and crawling strategies

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Analyze crawled data to identify patterns, gaps, and opportunities for improvement

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Build pipelines for data ingestion, analysis, and quality improvement

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Build specialized crawlers for high-value data sources

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Collaborate with Pretraining and Tokens teams to create feedback loops between crawled data and data evaluation results.

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Collaborate with team members on improving data acquisition processes

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Participate in code reviews and debugging sessions

You may be a good fit if you:

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Believe in the transformative potential of advanced AI systems

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Are interested in building a large-scale system to acquire all openly accessible information on the internet

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Have experience with data research, including designing experiments and analyzing results

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Have worked on web crawlers or large-scale data acquisition systems

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Are comfortable operating in a hybrid research-engineering role, balancing system building with experimentation

The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.

Annual Salary:
$320,000—$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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process