Nomiso - Senior LLM Engineer - Python / NLP

We are seeking an experienced NLP & LLM Specialist to join our team.

The ideal candidate will have deep expertise in working with transformer-based models, including GPT, BERT, T5, RoBERTa, and similar models.

This role requires experience in fine-tuning these pre-trained models on domain-specific tasks, as well as crafting and optimizing prompts for natural language processing tasks such as text generation, summarization, question answering, classification, and translation.

The candidate should be proficient in Python and familiar with NLP libraries like Hugging Face, SpaCy, and NLTK, with a solid understanding of model evaluation metrics.

Roles and Responsibilities :

• Model Expertise : Work with transformer models such as GPT, BERT, T5, RoBERTa, and others for a variety of NLP tasks, including text generation, summarization, classification, and translation.
• Model Fine-Tuning : Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering.
• Prompt Engineering : Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks.
• Iterate on prompts to optimize model performance.
• Instruction-Based Prompting : Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives.
• Zero-shot, Few-shot, Many-shot Learning : Utilize zero-shot, few-shot, and many-shot learning techniques to improve model performance without the need for full retraining.
• Chain-of-Thought (CoT) Prompting : Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations.
• Model Evaluation : Use evaluation metrics such as BLEU, ROUGE, and other relevant metrics to assess and improve the performance of models for various NLP tasks.
• Model Deployment : Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications.
• Bias Awareness : Be aware of and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs.
• Collaboration : Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions.

Must Have Skill :

Qualification :

(ref : hirist.tech)