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 knowledgebases 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 APIcreation.
Collaborate closely with Data Engineers to build and optimize data pipelines for model trainingand inference.
Work with DevOps Engineers to containerize (Docker), deploy (Kubernetes), and monitor modelswithin a CI / CD and MLOps framework.
Participate actively in an agile team, contributing to sprint planning, daily scrums, and codereviews to ensure timely delivery of high-quality AI features.
Required Technical Skills :
Expertise in Visual Large Language Models (VLLMs), Large Language Models (LLMs), and SmallLanguage 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 onbuilding and deploying AI / ML models.
Education :
Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field. AMaster's degree is preferred.
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