RELIX HR Consulting Pvt Ltd
5 days ago
Requirements:
· University degree in computer science, data science, artificial intelligence, or a related field. Advanced degree is desirable e Master, Ph.D.
· Hands on experience in Gen AI
· Proven experience (3+ years) in developing NLP models / Gen AI and systems, with a focus on prompt engineering or conversational AI.
· Collaboration with data scientists, machine learning engineers, and cross-functional teams will be crucial as you focus on creating high-quality prompts, refining model outputs, and enhancing the overall user experience.
· As a Prompt Engineer/Generative AI Engineer, your role is to design, develop, refine, and optimize AI-generated text prompts to ensure they are accurate, engaging, and relevant for various applications.
· It includes natural language processing (NLP) models and prompts that drive the performance and effectiveness of language models and conversational AI systems.
· Strong programming skills in languages such as Python, with experience in NLP libraries/frameworks
· Deep understanding of NLP algorithms, techniques, and architectures, including text classification, sentiment analysis, named entity recognition, language modeling, and dialogue systems.
· Experience with machine learning frameworks ie TensorFlow, PyTorch and deep learning techniques for NLP.
· Proficiency in data preprocessing, text normalization, tokenization, and other NLP-specific techniques.
· Strong analytical and problem-solving skills, with the ability to formulate NLP solutions for complex language understanding and generation tasks.
· Familiarity with prompt engineering techniques and methodologies, including designing and optimizing prompts to control model behavior and outputs.
· Experience in training and fine-tuning NLP models using large-scale datasets and relevant evaluation metrics.
· Knowledge of performance optimization techniques for NLP models, such as model compression, quantization, and inference efficiency.
· Strong collaboration and communication skills to work effectively in multidisciplinary teams and present findings to stakeholders.
· Up-to-date knowledge of the latest research papers, advancements, and trends in NLP.
· Experience with deploying NLP models in production environments and working with software engineering teams.
· Strong attention to detail, ability to work independently, and meet project deadlines.
· Publications in reputable NLP conferences or journals are advantageous.
· Performance Optimization - Optimize NLP models for speed, memory usage, and resource efficiency, enabling real-time or near-real-time responses.
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