Machine Learning

Doha Tax Free19 hours agoFull-time External
Negotiable
Role: Experience Level: 10+ Years location: QATAR Note :communication (Arabic & English). Gulf nationals only. Machine Learning & Generative AI Engineer (Mid-Level) • *ML | DL | Python | LangChain/LangGraph | Azure AI Foundry | RAG | Vector Stores | Semantic Kernel Role Summary Build and deploy enterprise-grade Generative AI solutions with strong grounding and measurable quality. You will implement RAG pipelines, agentic workflows (LangChain/LangGraph/ Semantic Kernel), and evaluation/monitoring on Azure AI Foundry and Azure services, or GCP. Key Responsibilities • Implement end-to-end RAG: ingestion, chunking, embeddings, retrieval, reranking, and citation/grounding. • Develop agentic workflows using Semantic Kernel, LangChain and LangGraph (tools, routing, memory) with guardrails and safe tool use. • Integrate vector stores/search (Azure AI Search vector, Pinecone, Weaviate, Milvus, pgvector, or equivalent) and maintain reliable data pipelines. • Build Python services/APIs (FastAPI preferred) with streaming, auth (Entra ID/OIDC as applicable), and production-ready error handling. • Own quality and operations: golden datasets, automated regression evaluation, tracing/observability, and latency/cost optimization (caching, batching). Required Qualifications • 3-6 years software engineering experience; 1-3 years delivering ML/GenAI features to production. • Strong Python, API development, unit/integration testing, and Git-based workflows (Azure DevOps or GitHub). • Hands-on experience with RAG patterns, embeddings, retrieval strategies, prompt design, and LLMs evaluation basics. • Experience with Azure AI Foundry / Azure OpenAI and deploying on Azure (Container Apps, Functions, App Service, • or AKS). • Comfortable working with data and documents; strong communication and documentation skills. Great Advantage • LLMOps: prompt/version governance, tracing (LangSmith/OpenTelemetry), and evaluation frameworks. • Hybrid search and reranking, structured outputs (JSON schema), and prompt- injection/tool-safety mitigations. • Performance testing and cost optimization experience for LLM-based systems. • Bilingual communication (Arabic & English). Typical Tech Stack • Python (FastAPI), LangChain, LangGraph, Azure AI Foundry, Azure OpenAI, Azure AI Search (vector), Semantic Kernel, PyTroch, Keras, Tensorflow. • Pinecone/Weaviate /pgvector / Azure AI Search, Docker, Azure DevOps, Key Vault, Application Insights.** Skills: vector,python,rag,kernel,ml,azure