Prompt Engineer at Siemens Technology and Services Private Limited

Posted on (6 months ago)

Location: Bengaluru, India

Industry: Software Development

Job Type: full-time

Experience Level: entry-level

Remote: hybrid

Job Description

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.

Responsibilities

  • Model Configuration: Configure the AI model with appropriate prompts and parameters.
  • Fine-tuning: Fine-tune pre-trained models on specific datasets.
  • Prompt Engineering: Craft effective prompts that elicit the desired responses.
  • Performance Optimization: Continuously optimize the model's performance.
  • Data Management: Handle data related to prompts and model inputs effectively.
  • Monitoring and Debugging: Monitor model behavior and identify issues.
  • Scaling and Deployment: Deploy AI models in production environments.
  • Ethical Considerations: Be aware of ethical considerations, such as bias, fairness, and privacy.
  • Documentation: Maintain documentation of prompt configurations, model versions, and best practices.
  • Collaboration: Collaborate with cross-functional teams.

Requirements

  • Natural Language Processing (NLP): Proficiency in NLP concepts and techniques.
  • Deep Learning: Understanding of deep learning fundamentals.
  • Programming Languages: Strong programming skills, particularly in Python.
  • Model Fine-tuning: Experience with fine-tuning pre-trained language models.
  • Prompt Design: Ability to design effective prompts.
  • Data Handling: Skills in data preprocessing, data management, and data encoding.
  • Performance Optimization: Knowledge of techniques to optimize the quality and diversity.
  • Deployment: Experience in deploying AI models in production environments.
  • Ethical AI: Awareness of ethical considerations in AI.
  • Collaboration and Communication: Strong teamwork and communication skills.
  • Monitoring and Debugging: Proficiency in monitoring model behavior and debugging issues.
  • Documentation: Ability to maintain clear and organized documentation.

Benefits

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