I am Nikhil Prasad, a Results‑driven Prompt Engineer with a strong foundation in AI research and development, and a keen interest in Cloud Security Engineering. Proven track record in enhancing user engagement and respon…
I am Nikhil Prasad, a Results‑driven Prompt Engineer with a strong foundation in AI research and development, and a keen interest in Cloud Security Engineering. Proven track record in enhancing user engagement and response rates through innovative prompt engineering and fine‑tuning large language models. Demonstrated expertise in integrating industry‑specific terminology and per‑formance monitoring to drive strategic decision‑making. Skilled in utilizing industry‑leading APIs and building AI‑powered applica‑tions. Possesses robust technical, security, and soft skills, with a strong academic background in Computer Science. Recognized for outstanding project work and contributions to AI and machine learning. Eager to leverage expertise in AI to further advance in cloud security engineering.
• Prompt Design: Design and develop prompts that prompt users to provide specific information or perform certain actions.
• Domain Knowledge Integration: Work closely with subject matter experts to incorporate domain‐specific terminology and knowledge into prompts
• Performance Monitoring: Track the performance of prompts in real‐world interactions and analyze data to identify areas for improvement.
Innovated and fine-tuned interactive prompts, boosting response rates by 10% and streamlined the data collection process for improved customer insights and strategic decision-making.
Collaborated with subject matter experts to integrate industry-specific terminology, enhancing prompt accuracy by 25% and improving user engagement metrics by 15%.
Tracked the performance of prompts in real-world interactions and analyzed data to identify areas for improvement.
Implemented advanced APIs including Gemini, OpenAI, and Hugging Face into Langchain initiatives, resulting in a 30% boost in AI performance and reducing development time by 35%, leading to faster project completions.
Built Streamlit NER app and QA app using Langchain tech.
Annotated CUAD datasets and fine-tuned SpaCy and LLM models.
Mastered prompt engineering techniques to optimize large language model outputs, resulting in a 40% increase in response accuracy and a 25% reduction in processing time.
Key Skills: NLP Algorithm, NER, Document Annotation, prompt engineering, Langchain, Spacy, Hugging-face.
Worked on platforms and multiple projects like Outlier, OpenTrain, and Remotasks.
Worked on AI Data Training and Data Labeling with the help of Annotation tools.
Collaborated with subject matter experts and multiple small-scale businesses to integrate industry-specific terminology, enhancing prompt accuracy by 25% and improving their engagement metrics by 15%.
Tracked the performance of prompts in real-world interactions and analyzed data to identify areas for improvement.
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