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    Engineering - Scientist/Engineer - San Francisco, CA, United States - Karkidi

    Karkidi
    Karkidi San Francisco, CA, United States

    1 week ago

    Default job background
    Description
    As a research engineer, you will build and maintain infrastructure used by the whole team, including yourself.

    You'll touch all parts of our code and infrastructure, whether that's making the cluster more reliable for our big jobs, improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling.

    You're motivated to understand our research so you can write code that accelerates it.
    Our recent progress, presented in

    Towards Monosemanticity:

    Decomposing Language Models With Dictionary Learning, makes us believe that the main blocker to LLM interpretability, known as superposition, has transitioned from an open research question to primarily an engineering challenge.

    Some of our team's notable publications include

    Towards Monosemanticity:

    Decomposing Language Models With Dictionary Learning, A Mathematical Framework for Transformer Circuits, In-context Learning and Induction Heads, and Toy Models of Superposition.

    This work builds on ideas from members' work prior to Anthropic such as the original circuits thread, Multimodal Neurons, Activation Atlases, and Building Blocks.

    Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems. Our interdisciplinary team has experience across ML, physics, policy, business and product.
    Have significant software engineering experience
    Want to learn more about interpretability research
    High performance, large-scale ML systems
    Language modeling with transformers


    Representative Projects:
    ETL pipelines for collecting and analyzing LLM activations at large scale
    Profiling and Optimizing ML Training, including parallelizing to many GPUs
    Writing a design doc for fault tolerance strategies
    Creating an interactive visualization of attention between tokens in a language model
    Familiarity with python is required for this role.

    Location-based hybrid policy: Currently, we expect all staff to be in our office at least 25% of the time.


    US visa sponsorship:

    We do sponsor visas However, we aren't able to successfully sponsor visas for every role and every candidate; operations roles are especially difficult to support.

    But if we make you an offer, we will make every effort to get you into the United States, and we retain an immigration lawyer to help with this.

    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're building have enormous social and ethical implications. Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
    ~ Comprehensive health, dental, and vision insurance for you and all your dependents.
    ~Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more
    ~ Stipends for education, home office improvements, commuting, and wellness.
    ~ Daily lunches and snacks in our office.
    ~ Relocation support for those moving to the Bay Area.

    Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
    ~ Private health, dental, and vision insurance for you and your dependents.
    ~ Pension contribution (matching 4% of your salary).
    ~Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more
    ~ Health cash plan.
    ~ Daily lunches and snacks in our office.

    The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial.

    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 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.

    We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.

    #
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