Azure AI/ML Engineer - LLM-Focused Fine-Tuning Expert (Hybrid, Lahore, USD Salary)

Requirements:

• Bachelors or Masters degree in AI, Data Science, or Computer Science
• Proven experience with PyTorch, TensorFlow; must have extensive experience in fine-tuning large language models such as Mistral, LLaMA, and Falcon.
• Proficiency in Azure AI Services, Kubernetes, and cloud-based AI deployment.
• Strong knowledge of Python, SQL, Flask, and JavaScript.
• Proficiency in ETL with Azure Data Factory and Databricks is a plus. Capable of building efficient data pipelines for real-time processing and scalability.
• Hands-on experience with MLflow, Jenkins, Docker, and CI/CD pipelines.
• Deep understanding of federated learning and scalable AI infrastructure.
• Effective communication skills, capable of leading cross-functional AI teams.
• Good to Have: Microsoft Azure AI Engineer Associate, AWS Certified Cloud Practitioner
• Experience in AI/ML Startups or R&D projects

Responsibilities:

• Build and optimize machine learning and deep learning models using PyTorch, TensorFlow, and Hugging Face.
• Develop and fine-tune transformer-based NLP models and LLMs including Mistral, Llama, and Falcon for domain-specific applications and advanced AGI systems.
• Deploy and manage AI/ML models on Azure Machine Learning Studio, Azure Kubernetes Service (AKS), and Azure Functions.
• Implement robust AI pipelines using Azure Data Factory, Synapse Analytics, and adhere to MLOps best practices.
• Design and implement search-optimized RAG-based AI models using vector databases such as FAISS, ChromaDB, Pinecone and other VectorDBs.
• Handle document processing, vector embeddings, and AI-powered knowledge retrieval systems.
• Create API-based AI solutions for automated finance, legal tech, and healthcare AI applications.
• Collaborate on AI orchestration and multi-agent AI systems to drive intelligent automation.
• Oversee AI/ML pipelines with DVC, MLflow, and CI/CD integration.
• Lead hyperparameter tuning, model retraining, and AI performance scaling.
• Ensure adherence to AI security, compliance, and ethical AI standards.