The Role
Design, fine-tune, and deploy LLMs/NLP models and RAG systems using Hugging Face, OpenAI, and LangChain. Build production AI services and APIs (FastAPI/Flask/Django), optimize vector search (FAISS, Pinecone, ChromaDB), and deploy scalable inference on cloud platforms with containerization.
Summary Generated by Built In
- Develop and fine-tune LLMs and NLP models using Hugging Face Transformers, OpenAI APIs, and LangChain.
- Implement retrieval-augmented generation (RAG) for intelligent AI-driven question answering and chatbot applications.
- Build and deploy AI models using FastAPI, Flask, and cloud-based inference engines (Azure ML, AWS SageMaker, GCP AI Platform).
- Optimize embedding search and vector retrieval using FAISS, Pinecone, and ANN-based search algorithms.
- Work on AI model deployment, API integration, and real-time AI application development in production environments.
Requirements
- Bachelor's or Master's degree in Artificial Intelligence, Computer Science, Data Science, or a related field.
- Atleast 2-4 years of experience in AI/ML development, NLP, or LLM-based application engineering.
- Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
- Strong experience with OpenAI APIs, LangChain, and fine-tuning LLMs for domain-specific applications.
- Expertise in developing and deploying AI-powered applications using FastAPI, Flask, or Django.
- Hands-on experience with cloud-based AI services such as Azure ML, AWS SageMaker, or GCP AI Platform.
- Knowledge of retrieval-augmented generation (RAG) and its implementation for AI-driven automation.
- Proficiency in working with vector databases like FAISS, Pinecone, and ChromaDB for efficient search and retrieval.
- Familiarity with containerization and orchestration tools such as Docker and Kubernetes for scalable AI deployment.
- Strong problem-solving skills with the ability to troubleshoot and optimize AI models for realworld performance.
- Excellent communication and teamwork skills to collaborate with AI researchers, engineers, and business teams.
Skills Required
- Bachelor's or Master's degree in AI, Computer Science, Data Science, or related field
- 2-4 years of experience in AI/ML development, NLP, or LLM-based application engineering
- Proficiency in Python
- Experience with TensorFlow, PyTorch, and Hugging Face Transformers
- Strong experience with OpenAI APIs, LangChain, and fine-tuning LLMs
- Expertise building and deploying AI applications using FastAPI, Flask, or Django
- Hands-on experience with cloud AI services such as Azure ML, AWS SageMaker, or GCP AI Platform
- Knowledge and implementation experience of retrieval-augmented generation (RAG)
- Proficiency with vector databases and embedding search: FAISS, Pinecone, ChromaDB
- Experience optimizing embedding search and ANN-based retrieval algorithms
- Familiarity with Docker and Kubernetes for scalable AI deployment
- Strong problem-solving, troubleshooting, communication, and teamwork skills
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The Company
What We Do
Pakistan Single Window (PSW) is an integrated digital platform that allows parties involved in trade to submit standardized information and documents with a single entry point to fulfill all import, export, and transit-related regulatory requirements, aiming to digitalize and streamline cross-border trade.
