Senior NLP Engineer - LLM

About Company :

Our teams have expertise in Full Stack Technologies, REST API Servers, Blockchain, DevOps, Cloud Technologies, Data Engineering, and Test Automation. We are building next gen SaaS platforms for e-commerce and health-tech domains.

About the Role :

We are seeking a highly skilled Senior NLP Engineer with expertise in large language models (LLMs), prompt engineering, and transformer-based architectures.

The ideal candidate will have strong experience fine-tuning, deploying, and optimizing advanced NLP models for real-world applications such as summarization, text generation, and question answering.

You will collaborate with cross-functional teams to design scalable, production-ready solutions while addressing challenges such as bias, hallucinations, and knowledge cutoffs.

Key Responsibilities :

- Fine-tune pre-trained models on domain-specific datasets to optimize for summarization, text generation, question answering, and related tasks.

- Prompt Engineering : Design, test, and iterate on contextually relevant prompts to guide model outputs for desired performance.

- Implement and refine instruction-based prompting strategies to achieve contextually accurate results.

- Apply zero-shot, few-shot, and many-shot learning methods to maximize model performance without extensive retraining.

- Leverage Chain-of-Thought (CoT) prompting for structured, step-by-step reasoning in complex tasks.

- Evaluate model performance using BLEU, ROUGE, and other relevant metrics; identify opportunities for improvement.

- Deploy trained and fine-tuned models into production environments, integrating with real-time systems and pipelines.

- Identify, monitor, and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs.

- Work closely with cross-functional teams (data scientists, engineers, product managers) to design scalable and efficient NLP-driven solutions.

Must-Have Skills :

- 4+ years of hands-on expertise with transformer architectures (GPT, BERT, T5, RoBERTa, etc.

- Strong understanding of attention mechanisms, self-attention layers, tokenization, embeddings, and context windows.

- Proven experience in fine-tuning pre-trained models for NLP tasks (summarization, classification, text generation, translation, Q&A).

- Experience with instruction-based prompting and Chain-of-Thought prompting for reasoning tasks.

- Proficiency in Python and NLP libraries/frameworks such as Hugging Face Transformers, SpaCy, NLTK, PyTorch, TensorFlow.

- Strong knowledge of model evaluation metrics (BLEU, ROUGE, perplexity, etc.

- Experience in deploying models into production environments.

- Awareness of bias, hallucinations, and limitations in LLM outputs.

Good to Have :

- Experience with LLM observability tools and monitoring pipelines.

- Exposure to cloud platforms (AWS, GCP, Azure) for scalable model deployment.

- Knowledge of MLOps practices for model lifecycle management.

Mandatory Key Skills :

2+ years in transformer-based NLP, 4+ years with GPT/BERT/T5/RoBERTa, expertise in fine-tuning, prompt engineering (zero/few/many-shot, CoT, instruction-based), strong Python & NLP frameworks (Hugging Face, PyTorch, TensorFlow, SpaCy, NLTK), and proven experience in model evaluation (BLEU, ROUGE, perplexity) & production deployment.

Industry Type : IT Services

Qualification :

7+ years in software/AI development with 2+ years in transformer-based NLP and 4+ years in hands-on work with GPT, BERT, T5, RoBERTa, and related architectures