LLM Engineer

3 days ago

Islamabad, Islamabad, Pakistan DCube Tech. Full time 600,000 - 1,200,000 per year

Designation:
LLM Engineer

Minimum Experience:
1.5–2 years industrial experience

Responsibilities

  • Research, fine-tune, and evaluate Large Language Models (LLMs) for conversational AI, summarization, retrieval-augmented generation (RAG), and document understanding.
  • Implement and optimize pipelines for context retrieval, prompt orchestration, and response generation.
  • Design and maintain embeddings-based retrieval systems using FAISS, Redis, or similar vector databases.
  • Integrate and test LLM APIs (e.g., OpenAI, Anthropic, Cohere, or local models via Hugging Face).
  • Develop modular and production-ready Python code following SOLID principles.
  • Manage model, data, and experiment tracking using DVC or MLflow.
  • Deploy LLM inference endpoints as microservices (FastAPI or Flask).
  • Collaborate with backend engineers to integrate LLM pipelines into existing applications.
  • Monitor performance, latency, and accuracy of deployed LLM-based systems.
  • (Preferred) Experience with model quantization, knowledge distillation, or retrieval optimization for low-latency deployments.

Requirements

  • 1.5–2 years of professional experience in NLP or applied LLM development.
  • Strong Python programming skills with hands-on production experience.
  • Proficiency with transformer-based architectures and Hugging Face ecosystem.
  • Familiarity with vector databases (FAISS, Pinecone, Weaviate, or Redis Vector).
  • Experience in developing RAG pipelines and integrating external data sources.
  • Comfort with Linux/Bash environments and version control (Git/GitLab).
  • Experience with Docker, API deployment, and model serving.
  • Fluency with modern AI-assisted coding tools (e.g., Cursor, GitHub Copilot, or similar).
  • Understanding of cloud platforms (AWS, Azure, or GCP) and GPU/compute environments.

Key Skills

Languages/Tools:
Python, Git/GitLab, Linux/Bash, Docker, DVC, MLflow, Cursor, Copilot

Frameworks/Libraries:
PyTorch, Transformers (Hugging Face), LangChain, LlamaIndex

LLM Operations:
RAG pipelines, Prompt Engineering, Embedding Models, Fine-tuning

Model Serving:
FastAPI, Flask, TorchServe

Databases:
FAISS, Redis Vector, Pinecone, Weaviate

Specialized Areas:
Contextual Retrieval, Model Optimization, AI Agent Frameworks

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