Prompt Engineer-AI models


Email Alerts

Subscribe to be the first to know about new Prompt Engineering Jobs

    We respect your privacy. Unsubscribe at any time.


    - Full Time

    Posted on: 13 September, 2023

    Prompt Engineer-AI models

    About Us

    The Center for Competence (CoC) team on Generative AI within Siemens Healthineers Development center is responsible for providing productivity gains for the Product development lifecycle for the R&D; organizations with a services, solutions and tool development to be used in the development of internal and external applications.


    The primary role is to harness the power of prompt-based AI models, such as GPT (Generative Pre-trained Transformer) models, to generate human-like text or responses to specific queries or tasks. These models have a wide range of applications, including natural language understanding, chatbots, content generation, and more. A Prompt Engineer is responsible for configuring and fine-tuning these models to produce desired outputs efficiently and effectively.

    Roles and Responsibilities:

    Model Configuration: Configure the AI model with appropriate prompts and parameters to achieve desired text generation outcomes. This involves understanding the specific use case and tailoring the model accordingly.

    Fine-tuning: Fine-tune pre-trained models on specific datasets to adapt them to the intended task or domain. This process requires expertise in transfer learning and data preprocessing.

    Prompt Engineering: Craft effective prompts that elicit the desired responses from the AI model. This may involve designing templates, specifying context, and optimizing prompt input.

    Performance Optimization: Continuously optimize the model’s performance in terms of output quality, coherence, and relevance. Implement techniques like temperature scaling, top-k sampling, and nucleus sampling to control the output.

    Data Management: Handle data related to prompts and model inputs effectively. Ensure data integrity, cleanliness, and appropriate encoding for input into the AI model.

    Monitoring and Debugging: Monitor model behavior and performance, identify issues, and debug problems as they arise. This includes addressing issues related to biased or inappropriate outputs.

    Scaling and Deployment: Deploy prompt-based AI models in production environments, ensuring they can handle a high volume of requests efficiently and reliably. Implement model versioning and monitoring.

    Ethical Considerations: Be aware of ethical considerations, such as bias, fairness, and privacy, and take steps to mitigate potential issues in the generated text.

    Documentation: Maintain documentation of prompt configurations, model versions, and best practices for prompt engineering. Share knowledge within the team.

    Collaboration: Collaborate with cross-functional teams, including data scientists, machine learning engineers, and domain experts, to align the model’s behavior with project objectives.

    Key Skills Required:

    Natural Language Processing (NLP): Proficiency in NLP concepts and techniques, including tokenization, text generation, and language modeling.

    Deep Learning: Understanding of deep learning fundamentals, especially transformer-based models like GPT.

    Programming Languages: Strong programming skills, particularly in Python, for scripting and model implementation.

    Model Fine-tuning: Experience with fine-tuning pre-trained language models and transfer learning techniques.

    Prompt Design: Ability to design effective prompts that produce desired AI model responses.

    Data Handling: Skills in data preprocessing, data management, and data encoding for AI model inputs.

    Performance Optimization: Knowledge of techniques to optimize the quality and diversity of generated text.

    Deployment: Experience in deploying AI models in production environments using cloud services or containerization.

    Ethical AI: Awareness of ethical considerations in AI, especially in text generation, and strategies to address biases and fairness issues.

    Collaboration and Communication: Strong teamwork and communication skills to work effectively with multidisciplinary teams and stakeholders.

    Monitoring and Debugging: Proficiency in monitoring model behavior and debugging issues in real-time.

    Documentation: Ability to maintain clear and organized documentation for prompt configurations and model performance.

    A skilled Prompt Engineer plays a crucial role in harnessing the capabilities of prompt-based AI models to deliver contextually relevant and high-quality text generation solutions across various domains and applications.

    ▶️ Prompt Engineer-AI models ️ Siemens India

    Share the job:

    Related Jobs

    Ai and Prompt Engineering Trainer
    Ai and Prompt Engineering Trainer

    Part Time - 🌎 Remote

    Machine Learning Engineer (L3+)
    Machine Learning Engineer (L3+)

    CHf85,000 - CHf105,000 Full Time - Zürich, Swiss