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    Applied Scientist - Seattle, United States - Katanemo

    Katanemo
    Katanemo Seattle, United States

    4 weeks ago

    Default job background
    Description

    Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about advanced machine learning techniques (including Generative AI ones) that can solve complex problems in building AI-native applications?

    Katanemo is on a mission to build intelligent infrastructure for developers building intelligent AI-native apps. We are at a critical inflection point, and believe that POC-type tools will gave way to thought out infrastructure systems that developers need to build production-grade AI apps. We are working on an exciting new infrastructure project needed by developers to create magical conversational experiences and ditch the clunky point and shoot systems of the past.

    The team at Katanemo built serverless compute at AWS and deep learning infrastructure for Bing commerce, and is bringing their expertise to bear for builders creating new AI-native apps. We are looking to add to our founding team an innovative and talented senior staff applied scientist that can help us further the "intelligence" part of our infrastructure service. We are well-funded and backed by one of the best VC partners in Silicon Valley.

    What will you be doing?

    • You will lead cutting edge research and development of NLU (transformer and otherwise) models and analytical solutions in machine learning (ML) that can be used for multi-task detection, intent classification, named entity recognition, etc.
    • You will implement and improve modeling tools, training recipes, and prototypes utilizing programming skills in Python, Java or C++.
    • You will report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. This includes meeting with and working backwards from customer requirements.
    • You will research the latest modeling techniques and stay current with advancements in the field.

    What you will bring?

    • We need someone willing to be fearless and more than willing to take on bold challenges
    • A Ph.D Degree in Computer Science, Machine Learning, Applied Mathematics or an equivalent highly technical degree
    • 5+ years of modeling experience in one or more the following areas: Natural Language Processing/Understanding (NLP/NLU)
    • Hands on experience developing, scaling and implementing machine learning using relevant programming languages (such as Python), state of the art deep learning frameworks and big data tools
    • Working knowledge of advanced ML techniques: Multi-task Learning, Transfer Learning, Reinforcement Learning as well as Unsupervised and Semi-supervised Learning
    • Experience with designing and shipping software products that leverage machine learning at scale
    • Excellent problem solving skills and ability to dive into learning algorithms, model architecture, evaluation metrics, and field testing scenarios
    • Comfort communicating and interacting with scientists, engineers and product managers as well as understanding and translating the science of AI and Machine Learning to a more general audience

    Who you will be working with?

    The team at Katanemo built serverless compute at AWS, deep learning infrastructure for Bing commerce, the data and infrastructure stack at Cloudera and Lyft and is bringing their expertise to bear for builders creating new AI-native apps. You will be working with folks that deeply care about your professional and personal growth, know how to have fun, take enough time off to recharge and bring equal amount of energy and commitment to their craft.

    Qualified applicants receive consideration for employment without regard to race, religion, color, national origin, ancestry, sex, gender, gender identity, sexual orientation, marital status, age, physical or mental disability or medical condition, genetic information, veteran status, or any other consideration made unlawful by federal, state, or local laws.

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