Experteer Overview
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In this role you will design, automate, deploy and operate ML and LLM systems for EY’s global teams. You will build robust, scalable ML/LLM infrastructure supporting end-to-end model lifecycles, with a focus on governance, security and automation. You will work across cross-functional teams to implement cutting-edge pipelines (RAG, vector stores) and modern orchestration. This is a hands-on opportunity to shape production ML/LLM platforms in a hybrid EY GDS environment.
Compensaciones / Beneficios
• Design, automate and operate ML/LLM systems in production
• Build and maintain scalable ML/LLM infrastructure for end-to-end lifecycle management
• Develop and optimize CI/CD pipelines for ML/LLM workflows
• Leverage Azure ML for training, deployment and model registry
• Implement RAG architectures and vector stores for retrieval-augmented applications
• Utilize frameworks like LangChain, LangGraph, AutoGen, Semantic Kernel for orchestration
• Develop APIs (Flask/FastAPI) to operationalize ML/LLM services
• Containerize workloads with Docker and deploy on Kubernetes (AKS)
• Collaborate with cross-functional and global teams to drive governance and reliability
• Monitor, log and ensure performance of ML/LLM systems
Responsabilidades
• 3+ years in ML Engineering, MLOps or related fields with production ML/LLM experience
• Strong experience with Azure Machine Learning (training pipelines, model registry, deployment, automation)
• Hands-on with MLflow for experiment tracking and lifecycle management
• Experience building CI/CD pipelines for ML/LLM workflows (Azure DevOps, GitHub Actions, GitLab CI)
• Experience with RAG architectures, embeddings, retrieval pipelines and vector stores
• Proficiency with LangChain, LangGraph, AutoGen, Semantic Kernel or equivalent tools
• Advanced Python skills with version control xpzdshu and testing
• API development experience (Flask, FastAPI)
• Azure or other cloud experience for AI deployment and orchestration
• Docker and Kubernetes (AKS preferred)
• Strong collaboration and communication skills
• Bachelor’s or Master’s in CS/Engineering/AI or related field
Requisitos principales
• Hybrid work model
• Flexible work-life integration
• Well-being programs including psychological support
• Volunteering opportunities
• Recognition and rewards programs
• Career development and training opportunities
Hay opciones de teletrabajo/trabajo desde casa disponibles para este puesto.