Job description
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.
Required Skill Profession
Computer Occupations