About this role
Summary: Develop, fine-tune, and integrate large language models into enterprise applications. Responsibilities include building data pipelines, designing RAG systems, and optimizing model performance for specific business tasks.
At NestifyTech Solutions, looking for a highly skilled LLM Engineer to develop, fine-tune, and integrate large language models (LLMs) into enterprise-grade applications. This role requires deep expertise in NLP, model architecture, prompt engineering, and deployment of LLMs at scale.
### Responsibilities:
- Fine-tune and optimize LLMs (e.g., GPT, LLaMA, Mistral) for specific business tasks.
- Build pipelines for data preprocessing, training, evaluation, and inference.
- Design retrieval-augmented generation (RAG) pipelines using vector databases.
- Integrate LLMs with downstream systems using APIs or microservices.
- Implement prompt engineering techniques for few-shot and zero-shot learning.
- Benchmark model performance and apply techniques for cost optimization and latency reduction.
- Ensure safety, fairness, and compliance in model outputs.
### Required Qualifications:
- Advanced degree (MSc/PhD preferred) in AI, Machine Learning, Computer Science, or related field.
- 3+ years in ML/NLP roles; 1+ year hands-on with LLMs.
- Strong experience with Hugging Face, OpenAI APIs, LangChain, or similar.
- Deep understanding of Transformer architecture and attention mechanisms.
- Familiarity with fine-tuning methods (LoRA, QLoRA, PEFT, RLHF).
- Proficiency with Python, PyTorch or TensorFlow.
### Preferred Qualifications:
- Experience deploying models in production using cloud services (AWS/GCP/Azure).
- Knowledge of vector stores (e.g., Pinecone, Weaviate, FAISS).
- Contributions to open-source LLM frameworks or research publications.