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    Generative AI/Large Language Modelling Engineer - Zug, Schweiz - SPHYNX Group

    SPHYNX Group
    SPHYNX Group Zug, Schweiz

    vor 5 Tagen

    Default job background
    Ganztags
    Beschreibung

    Responsibilities

    • Designing, developing, and implementing generative AI models and algorithms utilizing state-of-the-art techniques such as GPT, VAE, and GANs.
    • Collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.
    • Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.
    • Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation
    • Optimizing existing generative AI models for improved performance, scalability, and efficiency.
    • Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.

    Requirements

    • Master's degree or higher in Computer Science, Engineering, or a related field.
    • Proven experience in machine learning and artificial intelligence development.
    • Proficiency in programming languages such as Python, R, or Java
    • Experience with natural language processing (NLP) and large language modelling (e.g., BERT, GPT-3, GPT-4)
    • Understanding of deep learning architectures and techniques.
    • Strong mathematical and statistical background.
    • Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
    • Excellent problem-solving and critical-thinking skills.
    • Ability to work independently and in a collaborative team environment.
    • Good communication and presentation skills.

    Preferred Skills and Qualifications

    • Knowledge of distributed computing and big data technologies (e.g., Spark, Hadoop).
    • Previous work on real-world AI applications or projects.
    • Publications or contributions to the AI/ML community.

    Benefits

    • Competitive remuneration package adjusted to proven skills and experience;
    • Excellent working conditions;
    • Exposure to training and professional development capabilities, including the ability to engage in cutting-edge research;
    • Exposure to international clients and collaborators.
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