GPT

Term from Artificial Intelligence industry explained for recruiters

GPT (which stands for Generative Pre-trained Transformer) is a modern artificial intelligence technology that can understand and generate human-like text. It's like having a very smart digital assistant that can write, answer questions, and help with various tasks. Companies use GPT to create chatbots, write content, analyze text, and automate customer service. You might see it mentioned alongside terms like "ChatGPT" or "GPT-4" which are popular versions of this technology. Think of it as a powerful tool that helps businesses handle text-based tasks more efficiently, similar to how Microsoft Excel helps with numbers and calculations.

Examples in Resumes

Developed customer service solutions using GPT technology, reducing response time by 50%

Implemented GPT-4 and GPT-3 models for automated content generation

Led a team working with GPT and Large Language Models for text analysis projects

Typical job title: "AI Engineers"

Also try searching for:

Machine Learning Engineer AI Developer NLP Engineer AI Research Scientist Prompt Engineer AI Solutions Architect Natural Language Processing Engineer

Example Interview Questions

Senior Level Questions

Q: How would you ensure responsible and ethical use of GPT in a business setting?

Expected Answer: A senior candidate should discuss data privacy, bias prevention, content filtering, and having human oversight. They should mention setting up guidelines for appropriate use and monitoring system outputs.

Q: How would you approach scaling GPT implementation for enterprise-level applications?

Expected Answer: Should discuss managing costs, optimizing response times, handling multiple users, ensuring reliability, and implementing proper security measures. Should mention practical solutions for common enterprise challenges.

Mid Level Questions

Q: What are the key considerations when choosing between different GPT models for a project?

Expected Answer: Should discuss factors like cost, speed, accuracy needs, and resource requirements. Should demonstrate understanding of different use cases for various GPT versions.

Q: How do you evaluate the quality of GPT outputs?

Expected Answer: Should explain approaches to measuring accuracy, relevance, and appropriateness of responses. Should mention both automated and human evaluation methods.

Junior Level Questions

Q: What is prompt engineering and why is it important?

Expected Answer: Should explain that prompt engineering is about writing clear instructions for GPT to get desired results, and demonstrate basic understanding of how to structure effective prompts.

Q: What are the basic safety measures when working with GPT?

Expected Answer: Should mention content filtering, avoiding sharing sensitive data, and understanding the limitations of the technology. Should show awareness of basic security considerations.

Experience Level Indicators

Junior (0-2 years)

  • Basic prompt engineering
  • Simple integration of GPT APIs
  • Understanding of AI safety basics
  • Basic output quality assessment

Mid (2-4 years)

  • Advanced prompt engineering
  • Custom GPT model implementation
  • Performance optimization
  • Integration with existing systems

Senior (4+ years)

  • Enterprise-level AI implementation
  • AI strategy development
  • Team leadership and mentoring
  • Complex system architecture design

Red Flags to Watch For

  • No understanding of AI ethics and responsible use
  • Lack of knowledge about data privacy and security
  • Unable to explain basic GPT concepts in simple terms
  • No experience with real-world AI applications