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  • All offersLublinAI/MLLLM Data Scientist
    LLM Data Scientist
    New
    AI/ML
    Team Up

    LLM Data Scientist

    7 118 - 8 643 USDNet/month - B2B
    Type of work
    Full-time
    Experience
    Mid
    Employment Type
    B2B
    Operating mode
    Remote

    Tech stack

      AI

      regular

      LLM

      regular

    Job description

    As an LLM Data Scientist, you will be responsible for designing, developing, and deploying advanced NLP systems that leverage cutting-edge AI technologies. Your work will focus on areas like prompt engineering, agent-based AI, Retrieval-Augmented Generation (RAG), and optimizing large language models for performance and efficiency. You will also collaborate with cross-functional teams to tackle challenges related to AI ethics, safety, and risk mitigation.


    Your role

    • Design and implement next-generation agent-based AI systems utilizing large language models (LLMs).
    • Conduct prompt engineering to optimize the interaction between AI models and tasks.
    • Work on Retrieval-Augmented Generation (RAG) and information retrieval to enhance AI system capabilities.
    • Perform comprehensive LLM evaluation, including alignment, safety, applicability, and knowledge assessments.
    • Fine-tune and optimize LLMs using advanced techniques like LoRA and QLoRA to improve inference efficiency and performance.
    • Collaborate with teams across disciplines to address ethical, safety, and risk-related issues surrounding AI deployment.


    Offer

    • Long-term freelance contract
    • Solid market rates depending on seniority
    • Access to top-notch projects


    Requirements

    • Prompt Engineering: Expertise in designing prompts to optimize AI task performance.
    • AI Performance Analysis: Experience in evaluating and analyzing the performance of AI models.
    • LLM Evaluation: Proficiency in evaluating LLMs for knowledge, alignment, safety, and overall applicability.
    • Natural Language Understanding (NLU): Hands-on experience with NLU libraries and tools such as NLTK or models like GPT-3.
    • LLM Inference Tuning: Skilled in optimizing LLM inference using techniques like LoRA or QLoRA for greater efficiency.
    • LLM Fine-Tuning: Experience in fine-tuning large language models to improve specific task performance.
    • Cloud Platforms: Proficiency in working with cloud services (Azure, GCP, AWS) for deploying and managing AI models.


    Nice-to-Have Skills:

    • GCP Toolset: Familiarity with Google Cloud tools like BigQuery, Dataflow, Dataproc, Vertex AI, and Pub/Sub for processing and analyzing large datasets.
    • Advanced AI Research: Interest in staying updated with the latest advancements in AI, including ethical AI and responsible AI usage.
    All offersLublinAI/MLLLM Data Scientist

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