Job Title

Role Purpose / Summary: ** As a Senior AI/ML Engineer, you will be at the core of the Brio AI Factory, responsible for the hands-on development, training, and deployment of advanced artificial intelligence and machine learning models. You will implement the technical vision set by the Solutions Architect, building the high-performance AI components that power large-scale use cases and drive innovation. Key Responsibilities: ** • Develop, train, and fine-tune advanced AI/ML models, including LLMs, VLLMs, and SLMs, for specific project requirements. • Implement complex retrieval-augmented generation (RAG) systems, leveraging both knowledge bases and graph data structures. • Design and implement sophisticated prompts and agentic AI workflows to create intelligent, autonomous systems. • Write clean, production-grade Python code for model development, data processing, and API creation. • Collaborate closely with Data Engineers to build and optimize data pipelines for model training and inference. • Work with DevOps Engineers to containerize (Docker), deploy (Kubernetes), and monitor models within a CI/CD and MLOps framework. • Participate actively in an agile team, contributing to sprint planning, daily scrums, and code reviews to ensure timely delivery of high-quality AI features. Required Technical Skills: ** • Expertise in Visual Large Language Models (VLLMs), Large Language Models (LLMs), and Small Language Models (SLMs). • Deep understanding and practical experience with Knowledge RAG and Graph RAG patterns. • Advanced skills in Prompt Engineering, Model Fine-tuning, and Model Distillation. • Proficiency with Vector Databases (e.g., Pinecone, Milvus) and Graph Databases (e.g., Neo4j). • Experience in designing and building Agentic AI Models and multi-agent systems. Preferred Skills / Tools / Frameworks: ** • Proficiency with core Python data science libraries (e.g., Pandas, NumPy, Scikit-learn). • Experience with deep learning frameworks such as PyTorch or TensorFlow. • Familiarity with AI/ML platforms and tools on Azure (Azure Machine Learning, Azure OpenAI). • Experience with MLOps tools like MLflow for model tracking and lifecycle management. Experience Level: ** • 7 to 9 years in a hands-on software engineering or data science role, with a primary focus on building and deploying AI/ML models. Education: ** • Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field. A Master's degree is preferred.