Senior LLMops Engineer

Element Technologies is a company focused on AI solutions, and they are seeking a Senior LLMops Engineer to design, develop, and deploy AI applications. The role involves fine-tuning large language models, collaborating with cross-functional teams, and leveraging Azure services for scalable AI solutions.

Responsibilities:

• Design, develop, and deploy AI solutions leveraging cutting-edge tools, frameworks, and best practices
• Fine-tune and deploy Large Language Models (LLMs) such as OpenAI and Azure-based services to deliver scalable AI applications
• Implement and optimize Retrieval-Augmented Generation (RAG) architectures, leveraging vector databases for efficient data retrieval
• Write clean, maintainable Python code following software development best practices, including GIT workflows, code reviews, and CI/CD pipelines
• Collaborate with cross-functional teams to integrate AI solutions with existing data engineering pipelines and cloud infrastructure
• Build and manage containerized AI applications using Docker and Kubernetes for scalability and reproducibility
• Leverage Azure services for deploying, monitoring, and scaling AI applications in the cloud

Requirements:

• Strong proficiency in Python programming with a deep understanding of the software development lifecycle
• Expertise in working with LLMs, including fine-tuning, prompt engineering, and deployment
• Hands-on experience with RAG architectures and vector databases for knowledge retrieval
• Familiarity with SQL Server and/or Snowflake for data storage and retrieval
• Proficiency in Docker for containerization and Kubernetes for orchestration of containerized applications
• Solid understanding of Azure services for deploying and managing AI applications
• Experience with advanced optimization techniques for LLMs in production
• Exposure to managing and deploying large-scale AI systems in cloud environments
• Knowledge of best practices in logging, monitoring, and debugging AI workflows
• Ability to collaborate effectively with data engineering teams for seamless integration of AI pipelines