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    Data Annotator/AI Data Trainer - London, United Kingdom - Itechpost

    Itechpost
    Itechpost London, United Kingdom

    1 week ago

    Default job background
    Freelance
    Description

    Cohere is focused on building and deploying large language model (LLM) AI into enterprises in a safe and responsible way that drives human productivity, and creates magical new ways to interact with technology and real business value.

    Our goals are ambitious, but also concrete and practical.

    Every day, our team breaks new ground, as we build transformational AI technology and products for enterprise and developers to harness the power of LLMs.

    Collectively, we're driven by the belief that our technology has the potential to revolutionize the way enterprises, their employees, and customers engage with technology through language.

    Cohere's broader research team is world-renowned, having contributed to the development of sentence transformers for semantic search, dynamic adversarial data collection and red teaming, and retrieval augmented generation, often referred to as "RAG," among other technological breakthroughs.

    Cohere's operational leaders have built, scaled, and led multi-billion product lines and businesses at Google, Apple, Rakuten, YouTube, AWS, and Cisco.

    At Cohere, we're obsessed with language and technology— we believe we need great writers and developers and always will.

    We also believe that remarkable talent, enthusiasm, and creative thinking add up to great work.

    We're looking for someone with superb python and data science skills to join our team and help shape the future of language technology.

    The most successful candidate will be a quick learner who is excited to train our model by working on a wide variety of writing and code based prompts.

    Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans - by way of feedback.

    Our AI Data Trainers ensure that all samples fed to our AI model are well-written, technically sound and useful to the end user.

    By creating content that data scientists would find useful, working python, or on use cases you will be an essential component of improving our Large Language Model's performance for iterations to come, thus having a lasting impact on Cohere's tech.


    Please Note:
    This is role may require occasional work on-site at our Soho office in London, UK. We are looking for candidates who are able to commit 12-24 hours a week minimum to this project.
    As a AI Data Trainer, you will:
    Spend the majority of your time writing or reading/proofreading code and natural language to create perfect samples to train our models

    Raise the bar continually by writing new code that is of exceptional quality to solve a variety of tasks, with a particular focus on data analytics.

    2+ years of industry experience working on real-world data science problems and pipelines. You excel in data analysis and visualization.
    a meticulous coder with an eye for readability, with experience in python and industry standard data science packages (numpy, pandas, matplotlib, sqlite, or others)
    Able to use sql syntax writing and workflows
    You have good familiarity with file/data formats, such as markdown, json, xml, yaml, html
    You've spent time re-writing, proofreading, and giving feedback on others' code in a previous role. A curiosity about ML or AI or LLMs, (bonus points if you have any experience in these)
    Expert in web-based research skills that you've used for your code before
    Ability to follow complex instructions, navigate ambiguity and work independently in a remote or hybrid environment
    20-30 minute video interview

    • We value and celebrate diversity and strive to create an inclusive work environment for all. Cohere provides accessibility accommodations during the recruitment process. Should you require any accommodation, please let us know and we will work with you to meet your needs.
    A great selection of office snacks
    Performance-based incentives #J-18808-Ljbffr
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