? Experience: 5+ Years

? Work Mode: As per business requirements

We are looking for an experienced LLM Engineer with solid expertise in Large Language Models, Python, Generative AI, LLM fine-tuning, model optimization, and deployment.

The ideal candidate will be responsible for developing, fine-tuning, optimizing, and deploying LLM-powered applications and enterprise-grade AI solutions.

? Key Responsibilities:

- Design, develop, and deploy LLM-based applications and Generative AI solutions.
- Work with large language models such as OpenAI GPT, Google Gemini, Anthropic Claude, Llama, Mistral, or similar.
- Implement model fine-tuning, customization, and optimization techniques for specific business use cases.
- Work on LLM training, inference, evaluation, and deployment workflows.
- Implement techniques such as LoRA, QLoRA, PEFT, and quantization for model optimization.
- Develop prompt engineering strategies and optimize model responses for accuracy and relevance.
- Build RAG-based applications using embeddings, semantic search, and vector databases.
- Develop scalable APIs and integrate LLMs with enterprise applications and backend systems.
- Optimize LLM inference performance, latency, throughput, and resource utilization.




- Implement LLM evaluation, testing, monitoring, and observability frameworks.
- Ensure responsible AI practices, data security, and hallucination mitigation.
- Collaborate with data scientists, AI architects, and engineering teams to deliver production-ready AI solutions.

? Mandatory Skills:

- 5+ years of experience in AI/ML, NLP, or software engineering with relevant LLM development experience.
- Strong programming expertise in Python.
- Hands-on experience with Large Language Models (LLMs).
- Experience with GPT, Gemini, Claude, Llama, Mistral, or similar models.
- Strong understanding of Transformers architecture and Attention Mechanisms.
- Experience with LLM Fine-Tuning, Model Optimization, and Inference.
- Hands-on experience with Hugging Face Transformers and related libraries.
- Knowledge of LoRA, QLoRA, PEFT, and Quantization techniques.
- Strong understanding of Prompt Engineering and Context Management.
- Experience with RAG, embeddings, vector databases, and semantic search.
- Experience developing and deploying production-grade AI applications.
- Knowledge of REST APIs, FastAPI, and cloud-based deployment.

📌 LLM Engineer (Noida)
🏢 Aventra.AI
📍 Noida