Machine Learning Engineer - San Francisco, United States - NLP PEOPLE

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    At Truva, we're pioneering the future of SaaS technologies by harnessing the capabilities of Large Language Models (LLMs) to automate tasks, enhance workflows, and deliver unmatched efficiency.

    Founded by Gaurav, a two-time founder and Stanford alumnus, and Anuja, an MBA graduate from UC Berkeley's Haas School of Business, Truva embodies innovation and excellence.

    With a foundation built on 20 years of combined experience, from launching companies recognized in the Forbes Top AI 50 to leading technological advancements at FAANG, our leadership is at the forefront of developing cutting-edge ML solutions and infrastructures.


    Joining means becoming part of a forward-thinking team dedicated to transforming the tech landscape through the power of LLMs.


    Job Description:


    We are in search of a LLM ML Engineer who is passionate about driving innovation in generative AI and machine learning.

    The ideal candidate is someone deeply entrenched in the text domain, experienced in melding the capabilities of LLMs with traditional NLP algorithms to push the boundaries of what's possible in generative asset creation and game development.

    In this role, you'll work alongside our founders and a distinguished team comprised of Forbes 30 under 30 entrepreneurs, Stanford engineers, and Berkeley MBA graduates, all of whom have over a decade of experience in leading roles across the tech industry.


    Key Responsibilities:

    • Generative Asset Creation: Conduct ongoing research into cutting-edge methods for generating text-based content.
    • LLM Integration: Leverage the full potential of large language models, integrating them with conventional NLP techniques to innovate new applications and solutions.
    • Experimentation with Prompt and RAG Approaches: Experiment with prompt engineering and Retrieval-Augmented Generation techniques to enhance model performance and output relevancy.
    • Model Strategy Development: Experiment with various models to identify the most effective strategies for deploying different models across diverse business use cases, ensuring optimal outcomes and efficiency.
    • Trend Analysis: Stay updated with the latest trends in generative deep learning methods, ensuring Truva remains at the cutting edge of technological advancements.

    Required Skills:

    • Advanced Knowledge in

    Machine Learning:
    Deep understanding of machine learning, NLP, and generative models, especially LLMs.

    • Programming Proficiency: Expertise in Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
    • Research and Development: Strong background in conducting research and implementing findings into practical solutions.
    • Problem Solving: Exceptional ability to solve complex problems creatively and efficiently.
    • Communication: Excellent command of English, capable of articulating complex concepts clearly and effectively.
    • Collaboration: Proven track record of working effectively in team environments, contributing to innovative product development.

    Qualifications:

    • Extensive experience in machine learning engineering, with a focus on NLP and generative AI.
    • Proficiency in Python and ML frameworks (TensorFlow, PyTorch).
    • Demonstrable experience with LLMs, including implementation and innovation.
    • Strong portfolio showcasing previous projects in generative AI or related fields.
    • Excellent problem-solving, communication, and teamwork skills.


    This position presents a remarkable opportunity to merge your expertise in machine learning with your passion for innovation, contributing to pioneering projects at Be part of a team that's setting new standards in the SaaS industry through the power of technology.


    Company:
    Truva


    Qualifications:

    Language requirements:

    Specific requirements:

    Educational level:

    Level of experience (years):
    Senior (5+ years of experience)


    How to apply:
    Please mention NLP People as a source when applying


    Tagged as:
    Industry ,

    Language Modeling ,

    Machine Learning ,

    NLP ,

    Unspecified

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