Principal Machine Learning Engineer

Who are we?Equinix is the world's digital infrastructure company®, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.Help us challenge assumptions, uncover bias, and remove barriers-because progress starts with fresh ideas. You'll find belonging, purpose, and a team that welcomes you-because when you feel valued, you're empowered to do your best work.Job SummaryAs a Machine Learning Engineer, you will design, build, deploy, and scale machine learning and generative AI systems that power real-world products. You will work closely in AI Sidekick team and business teams to translate advanced ML and LLM capabilities into reliable, production-grade solutions across multi-cloud environments including GCP, AWS, and Azure.This role blends applied machine learning, software engineering, and MLOps, with a strong focus on building robust, scalable systems rather than purely academic research.ResponsibilitiesDesign, develop, and deploy machine learning and Large Language Model (LLM)-based solutions for production use casesCollaborate with Generative AI Center of Excellence leaders and business stakeholders to evaluate buy vs. build decisions for generative AI applicationsBuild and integrate agent-based workflows using platforms such as Google Agentspace, Microsoft Copilot, and Salesforce AgentforceDevelop end-to-end ML pipelines, covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoringArchitect and implement LLM-powered systems that integrate agents and services across multiple cloud platforms into a unified solutionOptimize ML workflows for performance, scalability, reliability, and cost efficiency in cloud environments (GCP, Azure, AWS)Implement and maintain MLOps best practices, including CI/CD, model versioning, experiment tracking, and automated retrainingWork