Research Engineer, Data Ingestion - San Francisco - Y-Axis

    Y-Axis
    Y-Axis San Francisco

    1 week ago

    $320,000 - $405,000 (USD) per year
    Description

    Overview


    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

    • Develop and maintain our large‑scale web crawler
    • Design and run experiments to evaluate data quality, extraction methods, and crawling strategies
    • Analyze crawled data to identify patterns, gaps, and opportunities for improvement
    • Build pipelines for data ingestion, analysis, and quality improvement
    • Build specialized crawlers for high‑value data sources
    • Collaborate with Pretraining and Tokens teams to create feedback loops between crawled data and evaluation results
    • Collaborate with team members on improving data acquisition processes
    • Participate in code reviews and debugging sessions

    Qualifications


    You may be a good fit if you:

    • Believe in the transformative potential of advanced AI systems
    • Are interested in building a large‑scale system to acquire all openly accessible information on the internet
    • Have experience with data research, including designing experiments and analyzing results
    • Have worked on web crawlers or large‑scale data acquisition systems
    • Are comfortable operating in a hybrid research‑engineering role, balancing system building with experimentation

    Compensation


    Annual salary: $320,000—$405,000 USD. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.

    Logistics


    Education requirements: 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. If we make you an offer, we will make every reasonable effort to get you a visa.

    Diversity & Inclusion


    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. This makes representation even more important, and we strive to include a range of diverse perspectives on our team.

    Culture & Impact


    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. 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.

    How to Apply


    Incase you would like to apply to this job directly from the source, please click here.


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