Prompt Engineering

ENFACTUM PTE. LTD.; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

A leading company in AI and NLP is seeking a Prompt Engineer to enhance prompt development and performance. This role involves collaborating with teams to create efficient GitHub Copilot prompts, optimizing strategies, and educating users on prompt engineering techniques. Applicants should have a strong background in machine learning and be able to communicate effectively with diverse stakeholders.

Qualifications

• Experience in NLP and machine learning is essential.
• Strong collaboration skills with product and engineering teams.
• Ability to develop and refine coding prompts effectively.

Responsibilities

• Develop and refine prompts to achieve coding goals.
• Collaborate with teams to translate user needs into prompts.
• Conduct experiments to identify best prompt practices.

Skills

Natural Language Processing

Machine Learning

Collaboration

Prompt Optimization

Job description

As a Prompt Engineer, your responsibilities include working with our content creators, product teams, and data scientists to develop and refine prompts, optimize prompt performance, and stay up-to-date on the latest advancements in AI, natural language processing, and machine learning.

Ultimately, you will work directly with development teams to create and improve prompts that enable more efficient usage of GitHub Copilot.

Responsibilities

1. Rapid Prompt Developing and Refinement: Develop and refine prompts to achieve specific coding goals, such as generating code snippets, fixing bugs, or writing unit tests.
2. Context and Constraint Management: Understand how to provide Copilot with the necessary context (e.g., code base, language, framework) and constraints (e.g., specific libraries, coding style) to guide its suggestions.
3. Prompt Experimentation and Testing: Conduct experiments to evaluate different prompt strategies and identify best practices.
4. Prompt Documentation and Library Creation: Create and maintain a library of effective prompts or prompt chains for various tasks.
5. User Education and Training: Develop tutorials and resources to help developers learn and improve their prompt engineering skills.
6. Feedback and Iteration: Analyze Copilot's responses and identify areas for improvement, suggesting updates to the model or prompting techniques.
7. Team Collaboration: Collaborate with product teams, data scientists, and engineers to understand user needs and translate them into effective prompts.
8. Prompt Experiments: Conduct experiments and research to test new prompting techniques and optimize existing workflows.
9. Staying Ahead on Strategy: Keep up with the latest advancements in NLP and AI, applying those insights to your work.
10. Documentation: Document and communicate your work clearly to both technical and non-technical audiences for future reference.