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Edison

    Technical Architect - Edison, United States - TEPHRA

    TEPHRA
    TEPHRA Edison, United States

    2 weeks ago

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    Description
    :

    Job Description:

    Strong and proven ability to identify and categorize use cases suitable for Generative AI usage and implementation. This is a key ask.


    • Responsible for reactive and proactive proposals responses for solutions involving Generative AI (specially LLMs), Conversational AI & cloud AIaaS.
    • Provide leadership for the transformation of customer requirements into visions, strategies, and roadmaps to implement Design AI enabled solutions, Data Science services platform at enterprise scale.
    • Strong expertise in the Data & AI architecture for one of the Cloudpartners -Azure, AWS, GCP
    • Develop and implement applications incorporating Generative AI models such as GPT, Anthropic Claude,, Google Palm, Meta Llama, focusing on enhancing developer and business productivity.
    • Knowledge of MLOPS will be beneficial.
    • Architect solutions incorporating Retrieval Augmented Generation, In-context Memory, Transformer Architectures, and Hierarchical Models, ensuring optimal model performance and scalability.
    • Apply middleware frameworks such as LangChain and Llama Index for efficient indexing, retrieval, and chaining of language models, enhancing the contextual understanding and response generation of applications.
    • Integrate multiple components such as data processing, machine learning models, and feedback mechanisms to address architectural challenges and ensure flawless deployment.
    • Keep abreast of emerging trends, sophisticated patterns, dependencies in data, and advancements in AI architecture, supplying to the refinement and innovation of application development processes.
    • Explore and implement inference techniques in generative AI for making predictions or generating new data based on observed input.
    Qualifications:

    Hands-on programming skill on at least one language

    Strong hands-on capabilities on "Artificial Intelligence" and "Machine Learning" PaaS components such as:


    • Contextual Conversation design- for personalized and humanized interaction with end user for complex business cases
    • Microsoft BOT service, Google DialogFlow EX, Amazon Lex
    • NLP model - design, training and publishing for multiple languages
    • Project experience and/or skills Certification with generative AI including
    :

    Azure Open AI (GPT 3.5/4) , Google PaLM 2 and AWS Bedrock


    • Custom Speech model - Speech-to-text and Voice synthesis calibrated for language, accent, pitch, tone, noise and business vocabs.
    Standard Architectural Practices As Below:


    • Omni-Channel Integration for AI. MLOPS knowledge.
    • Deployment and publish for AI and ML services with ACR, ACI, Docker, Azure Kubernetes
    • Azure/ AWS/ GCP certifications, AWS Machine Learning Specialty, Google Certified Cloud Engineer and certifications on LLMs, prompt engineering
    • Web app and services - Micro services, Azure functions, Logic apps, API management
    #LI-MG2
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